| | Source-ID in "FL-###" format. ("FL" are the first and last initials of the person who did the evaluation, and ### is the source number for that person. | Date Entered | What domain is this source for? (Policy, Economics, Psychology, etc.):
| What question (within the domain) does the source address?
| What is the source title (title of the article)? | Who is (are) the author(s) of the source? | Provide the complete reference. (For example, for an article: journal name, volume, issue number, pages or article number, year.) | Provide the source's DOI. | Provide the journal’s most recent Web of Science Quartile (write quartile and year, e.g. Q1 (2017)) | Provide the journal’s most recent Web of Science Impact Factor. (Give the impact factor with the year in parentheses. e.g. 3.5 (2016)) | Provide the number of times the article was cited (based on Web of Science). | Was the source peer reviewed? (Yes, No, Don't Know) | Briefly in 1-2 sentences, why did you include this article? | What is (are) the broad research question(s)? | What are the researchers' hypotheses? | Is this a meta-analysis or systematic review paper? (Y/N) **If "Y" STOP HERE | How many studies were included in the paper? | How many studies in the source were experimental? | How many studies in the source were correlational? | Which study are you evaluating currently? (e.g. Study 1) | What is the sample size of the study? | Is the study cross-sectional or longitudinal? (CS/L) | If longitudinal, what is the time frame? | For an experimental study, what is (are) the independent variable(s)? For a correlational study, what is (are) the theorized predictor variable(s)? | How were the variables in column X measured? | How well does this measurement capture the conceptual variable? (Not Well At All = 1, Not Well = 2, Neutral = 3, Somewhat Well = 4, Very Well = 5) | In your opinion, is this a suitable way to measure the variable in column Y? (Y/N/IDK) | What manipulation(s) was (were) performed? | Was a control group included? (Y/N) | If a control group was included, what was the control group? | Was there random assignment to different conditions? (Y/N) | For an experimental study, what is (are) the dependent variable(s)? For a correlational study, what is (are) the theorized outcome variable(s)? | How were the variables in column AG measured? | How well does this measurement capture the conceptual variable? (Not Well At All = 1, Not Well = 2, Neutral = 3, Somewhat Well = 4, Very Well = 5) | In your opinion, is this a suitable way to measure the variable in column AG? (Y/N/IDK) | Were there other variables measured that were not included in the hypotheses? (Y/N) | If yes, what were they? | Can causal claims be made based on the methodology of this study? (Y/N) | Did the authors make causal claims? (Y/N) | What correlational/associational claims were made? | Which hypotheses were supported by the data? | Which hypotheses were not suppored by the data? | Did the authors attempt to rule out potential alternative explanations for their results? (Y/N) | If so, how? | Are the results generalizable? (Y/N/Kind Of/IDK) (Look back at your assessment of the measurement of variables relative to the conceptual variable and the sample compared to the population discussed in conclusions) | What were the key limitations listed by authors? | Look back at Columns E, O, and P. Does the domain question conceptually match the source's research questions? (Y/N) | What is your assessment as to which side of the case this source supports? State either "Pro: " or "Con: " or "Both: " or "Neither: " followed by an explanation of your reasoning. | What is your assessment of the overall utility of this study for the Science Court Case?
On a scale of 1-10, how relevant are the findings for answering the domain question (Not relevant at all = 1, Extremely relevant = 10)? | What is your assessment of the overall scientific quality of this study?
On a scale of 1-10, how well do you think the methods operationalize the research questions? (Not well at all = 1, Extremely well = 10)? | Final recommendation:
This study should be admitted as evidence in the Science Court trial. (Y/N) |
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
|---|
| Colin | CB-001 X | 10/2/18 | Educational Impact (Equity across skill levels) | Does computer assisted learning close the achievement gap between high and low performing students? | Remedying Education: Evidence From Two Randomized Experiments in India | Banerjee, A. V.
Cole, S.
Duflo, E.
Linden, L. | Quarterly Journal of Economics 122 1235-1264, 2007 | 10.1162/qjec.122.3.1235 | Q1 | 7.863 | 234 | Yes | This details a rigorous study in which it was shown that computer assisted learning can help the lowest achieving students in an impoverished community in India improve language and math skills. | 1. Can the provision of information and communication technologies, particularly computers and software that adapts to the user's skill level, improve learning for the lowest achieving students in a poor community?
2. How effective is differentiated instruction from a computer compared to a teacher?
3. Are any gains from differentiated instruction due to class size, or is the treatment what drives improvements? | The researchers hypothesized that, unlike other inputs such as new textbooks and school lunches, computers with adaptive software would help the lowest achievers learn core competencies that they failed to acquire in previous school years. | N | 2 | 2 | 0 | Study 2 | Year 1: Not implemented
Year 2: 111 schools, 5,945 students
Year 3: Same as Year 2 | L | 3 years | Study 1: Access/no access to a Balsakhi
Study 2: Access/no access to adaptive math software | It's a control group/treatment group setup, so the variables are binary | 5 | Y | NA | Y | They used stratified sampling to assign schools to control/treatment groups based on pretest scores, gender, grade, and language of instruction. | Y | Score on posttest | Numerical grade | 4 | Y | N | NA | Y | Y | Usage of computer assisted learning software that adapts to the user's skill level improves math test scores for students that were many grades behind in math competency relative to a control group that used normal teacher-driven methods of instruction | There was only one | NA | Y | They returned to schools multiple times to administer posttest and went to absent students' houses if necessary to minimize affect of attrition.
Comparison of pretest results between control/experimental schools shows appropriate randomization of assignment.
For Balsakhi study, tested to ensure smaller class size was not a factor. | Kind Of | 3 years is too short to evaluate long term effect on learning and how school improvement affects labor market | Y | | 7 | 9 | Y |
| Blake | BP-001 | 10/2/18 | Implementation | What other "costs" exist when implementing a 1:1 program other than purchasing the physical devices |
Teachers’ Technology Competency and Technology Integration in 1:1 Schools | Nicholas J Sauers, Scott McLeod | JOURNAL OF EDUCATIONAL COMPUTING RESEARCH
Volume: 56 Issue: 6 Pages: 892-910
DOI: 10.1177/0735633117713021
Published:OCT 2018 | 10.1177/0735633117713021 | Q3 | 1.234 | 0 | yes | Highlights different "barriers" students and staff face when implementing a 1:1 program | 1. Do teachers at 1:1 schools report that they integrate technology differently than teachers at non-1:1 schools? 2. Do teachers at 1:1 schools report higher levels of technology competency than teachers at non-1:1 schools? | No hypothesis stated | N | 2 | 0 | 2 | Study 1 | 110 schools and 992 individual teachers from Iowa | CS | NA | Study 1: Schools with 1:1 program/not having a 1:1 program | Survery data collected via Qualtrics that was sent to teachers via email which was then used to create propensity scores | 4 | Y | NA | Y | Yes. Schools without 1:1 tech. But, since a random study was not possible, propensity scores were used as a means to find control schools that were very similar to the treatment schools. | N | Self-reported use/ integration of technology in classroom | The integration variable was created from 14 survey items. Teachers were asked to respond to questions about how they used various technologies in their classrooms. The response scale was a 4-point scale that ranged from Not at all to Large extent. The 14 items were used to generate a raw score by adding the items together. The maximum possible integration score was 56.00 and the minimum score was 14.00, with a mean overall score of 27.33. The 1:1 teachers had a mean score of 30.38 and their non-1:1 peers had a mean of 25.73. These scores are a bit challenging to interpret, however, and they do not account for other variables that may impact integration scores such as age, content area, and school-level variables. To generate a more interpretable score, the statistical program Stata was used to convert raw scores into a standard deviation variable, which centered the scores on zero. The new integration variable is interpreted as the increase or decrease in standard deviations. | 4 | Y | Y |
Model 2 added teacher variables, and the final model added school and teacher variables. | Y | Y | The 1:1 teachers in the study reported significantly higher (p < .001) integration and competency scores on the teacher survey than their non-1:1 peers. Each of the six models revealed the same substantive results. | NA | NA | N | NA | Kind of | Not able to look at effectiveness of implemented technology in terms of student performance or take into account the many other variables/experiences the teachers have been exposed to to affect one's competency and willingness to implement in classrooms. Also, self-reported survey data is prone to bias from teachers most likley inflating their competency. | Y | Pro, evidence showing that 1:1 schools have higher rates of use of technology actually integrated into the classroom and teachers have higher reported competencies. | 6 | 7 | Y |
| Ryan | RJ-001 | 10/2/18 | Mental Health: Social Skills & Hyperactivity | The effect of more screen time on student mental health | Screen-based sedentary behaviour and psychosocial well-being in childhood: Cross-sectional and longitudinal associations | Allen, MS (Allen, Mark S.) ; Vella, SA (Vella, Stewart A.) | Mental Health and Physical Activity, Volume: 9, Pages: 41-47, 2015 | 10.1016/j.mhpa.2015.10.002 | Q3 | 2 | 3 | Don't know | Because it shows how more screen time use in young children leads to a poorer psychoscocial well-being | Is there an association between screen-based sedentary behaviour and psychosocial well-being in early and late childhood? | There is reason to consider that excessive screen-based sedentary behaviour might contribute to the onset of psychosocial difficulties in childhood. | N | 1 | 0 | 1 | Study 1 | 4242 | CS/L | 2 Years | Total Screen Time | The primary parent reported the number of minutes the child spends watching television and playing electronic games on an average week day and on an average weekend day. These values were weighted | 3 | IDK | Weekday hours were weighed heavier than weekend day hours | N | NA | N | Psychosocial Well-Being | The strengths and difficulties questionnaire (SDQ; Goodman, 1997 ) is a brief behaviour measure that covers common forms of child ill- and well-being including emotional, hyperactivity and conduct problems.In the current investigation the questionnaire was completed by the child's primary parent. | 3 | IDK | Y | Sex, Indigenous status, main language, parental education, socioeconomic postition, household income, general health, and pubertal status were all measured | Y | Y | screen time was negatively associated with prosocial behaviour, and positively associated with hyperactivity, emotional symptoms, peer problems and conduct problems. Also supporting hypotheses, screen time was positively associated with the development of emotional symptoms in young children, and positively associated with the development of hyperactivity and conduct problems in older children. | H1 | NA | N | NA | Kind of | The study used parent-report measures that are open to response bias (e.g., social desirability). The study was non-experimental meaning we can only speculate on causal connections. | Y | Con: This study shows that higher screen time negatively affects psychosocial skills in children | 7 | 5 | Y |
| Ryan | RJ-002 | 10/2/18 | Mental Health: | Effect of changes in screen time on mental health | Longitudinal associations between changes in screen-time and mental health outcomes in adolescents | Babic, MJ (Babic, Mark J.)[ 1 ] ; Smith, JJ (Smith, Jordan J.)[ 1 ] ; Morgan, PJ (Morgan, Philip J.)[ 1 ] ; Eather, N (Eather, Narelle)[ 1 ] ; Plotnikoff, RC (Plotnikoff, Ronald C.)[ 1 ] ; Lubans, DR (Lubans, David R.) | Mental Health and Physical Activity, Volume: 12, Pages: 124-131 2017 | 10.1016/j.mhpa.2017.04.001 | Q3 | 2 | 4 | Don't know | I choose this because it distinguishes recreational and non-recreational screen time use in kids. Which is an important distinction for our case | What are the longitudinal associations between changes in screen-time and mental health | We hypothesized that changes in recreational screen-time will be: (1) negatively associated with changes in physical self-concept and psychological well-being; and (2) positively associated with changes in psychological difficulties, after controlling for potential confounders. and (3) That non-recreational screen-time would not be associated with mental health outcomes. | N | 1 | 0 | 1 | Study 1 | 322 | L | 6 Months | Total Screen Time | Screen-time was measured using the Adolescent Sedentary Activity Questionnaire (ASAQ) | 4 | Y | NA | N | NA | N | Physical self-concept, psychological well-being, ill-being (emotional symptoms, conduct problems, hyperactivity, peer relationship problems) | The physical self-concept subscale from Marsh's Physical Self-Description Questionnaire ( Marsh, 1996 ) was used to provide a measure of self-concept in the physical domain. Deiner and colleagues' Flourishing Scale ( Diener et al., 2010 ) was used to measure participants' psychological well-being. To measure ill-being, participants completed the Strength and Difficulties Questionnaire | 4 | Y | N | NA | Y | Y | Changes in total recreational screen-time and tablet/mobile phone use were negatively associated with physical self-concept. No associations were found between any of the indicators of mental health and changes in screen use for homework. | H1,H3 | H2 | Y | Alternatively, the negative effect of screen-time on mental health may be due to the displacement of opportunities to participate in activities that promote mental health. Such activities may include sleep, physical activity or social activities . | Y | With few objective measures of screen-time that can be feasibly be used for research, recreational screen-time was measured by self-report which remains a significant challenge in accurately assessing sedentary behavior due to the possibility of recall and social desirability biases. | Y | Both: Shows that higher recreational screen time negatively affects physical self-concept, however there were no associations with non-recreational screen time and mental health. Non-recreational screen time being time using a computer to do homework. | 7 | 7 | Y |
| Blake | BP-002 | 10/2/18 | Implementation | What other "costs" exist when implementing a 1:1 program other than purchasing the physical devices | Exploring challenges faced by different stakeholders while implementing educational technology in classrooms through expert interviews
| Sie Wai Chew, I-Ling Cheng, Kinshuk, Nian-Shing Chen | Journal of Computers in Education
June 2018, Volume 5, Issue 2, pp 175–197 | : https://doi-org.ezp1.lib.umn.edu/10.1007/s40692-018-0102-4 | NA | .72 (2016) | 0 | Yes | Relates directly to my domain but is not a "study" but rather interviews and other qualitative data that can not be used at this point. However, this will be very helpful in the future. | identifying the underlying challenges and issues faced by the different users groups involved in the technology implementation processes (i.e., learners, teachers/educators, schools/universities, developers and researchers) | In analyzing the content of these interview sessions, this study conducted a qualitative content analysis. The research conducted a qualitative content analysis which involved using a systemic method to analyze the qualitative data retrieved from the interviews, and objectively describe and interpret the interview content’s meaning in identifying the different challenges faced by different stakeholders during the implementation experiences, and other suggestions provided by the experts | Y | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | CON, will be very useful in making the case that this proposed intiative has a wide variety of stakeholders and gives examples of concerns specific to each stakeholder group | 9 | | |
| Blake | BP-003 | 10/2/18 | Implementation | What other "costs" exist when implementing a 1:1 program other than purchasing the physical devices | Integrating technology into K-12 teaching and learning: current knowledge gaps and recommendations for future research | Khe Foon Hew, Thomas Brush
| Educational Technology Research and Development
June 2007, Volume 55, Issue 3, pp 223–252 | https://doi-org.ezp1.lib.umn.edu/10.1007/s11423-006-9022-5
| Q2 | 1.728 | 454 | Yes | I chose this because it helps to identify the common barriers schools experience when looking to implement a 1:1 program and how to overcome these barriers and at what costs | The focus of our technology integration literature search and discussion in this paper is on the general barriers affecting the use of computing devices in K-12 schools for instructional purposes, and the strategies to overcome those barriers. | No hypothesis stated | Y | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | CON, highlights the 6 main categories comprised of 123 total barriers associated with implementing such a program, all of which present a legitamate concern to individuals and schools looking to do this | 9 | | |
| Blake | BP-004 | 10/2/18 | Implementation | What other "costs" exist when implementing a 1:1 program other than purchasing the physical devices | Examining the Role of Professional Development in a Large School District's iPad Initiative | Min Liu, Yujung Ko, Amanda Willmann & Cynda Fickert | Journal of Research on Technology in Education, October 2017, Volume 50, pp 48-69 | | Q1 | 2.12 | 0 | Yes | Chose this because it is a study using both quantitative and qualitative data with explicit methodologies and research questions regarding staff development | 1. What are teachers' views of the district-provided PD? Do their views change during the year-long iPad initiative?
2. Do teacher characteristics (i.e., gender, years of teaching, school levels, mobile device ownership, length of owning a device, view of mobile learning, and mobile technology self-efficacy) relate to their views on PD? If so, in what way?
3. How do teachers use iPads in their classroom while and after receiving district-provided PD? Are there any shifts in their use? | No hypothesis stated | N | 1 | 0 | 1 | Study 1 | 342 | L | 1- year | district-provided PD teachers received>> but also, (i.e., gender, years of teaching, school levels, mobile device ownership, length of having mobile device[s], teach- ers’ perception on mobile learning, and their mobile technology self-efficacy) | measured participation in district-provided PD (took attendance) also administered test of proficiency to teachers at end of training, other ind. variables measure with questionnaires, interveiws, scales | 4 | Y | NA | N | NA | N | RQ1: Teachers' Views About PD and Change Over the Implementation Year RQ2:Relationship Between Teacher Characteristics and Their Views on PD RQ3: iPad Uses in Classrooms While/After Teachers Received PD | RQ1: Likert scale of 1-5 and interviews RQ2: Multiple regressions/correlations RQ3: Interviews and open-ended questionnaires | 4 | Y | Y | Two additional factors that significantly influenced teachers' view toward PD were identified: mobile device ownership and school level. More specifically, teachers who owned mobile devices for more than 1 year tended to have less positive views toward PD training compared to those who owned mobile devices for less than a year. It is possible those teachers owning mobile devices for fewer years were less familiar with the devices and therefore they would need more training to use the device in instruction and thus found PD useful. High school teachers had less positive views than elementary school teachers. | Y | Y | Professional development accompanying any technology initiatives is an important factor affecting whether and how teachers use technology in their classrooms. | NA | NA | N | NA | Y | It is necessary to keep in mind that in terms of context, this study is situated in one, though large, school district in the United States with its participating teachers. Some significant changes as shown in ANOVAs with repeated measures are relatively small, and the factors from multiple regression analyses are preliminary. More studies are therefore needed. Research is also needed to understand how teachers' characteristics may possibly relate to their PD needs, especially looking at how to design PD training for teachers at different school levels, recognizing that high school teachers' needs for mobile technology integration will be quite different from teachers at other levels. In this study, the school district only provided one iPad to its teachers. The limited number of the device has most likely limited teachers' use. It is necessary to examine what happens if teachers have more devices for their classroom use and especially what happens if the district also provides the device to their students or allows BYOD (bring your own device), as more and more schools are adopting that policy | Y | CON- Professional development accompanying any technology initiatives is an important factor affecting whether and how teachers use technology in their classrooms. This research confirms the characteristics of effective PD as indicated in the literature but has also identified several factors of importance in order to achieve successful PD training accompanying any technology initiatives. This study also provided a detailed account of teachers' practices in using iPads in their instruction while and after they received the PD. | 7 | 8 | Y |
| Colin | CB-002 | 10/2/18 | Education Impact (Equity across skill levels) | How do 1:1 programs fair in economically disadvantaged communities? | Effects of Technology Immersion on Middle School Students' Learning Opportunities and Achievements | Shapley, K., Sheehan, D., Maloney, C., and Caranikas-Walker, F. | Journal of Educational Research 104 299-315, 2011 | 10.1080/00220671003767615 | Q3 | 1.239 | 20 | Yes | This article presents a quantitative study of 42 schools in Texas, pairing 21 schools with a 1:1 program and 21 without after Texas' Technology Immersion pilot program in the early 2000s launched. It is a longitudinal study, providing data on student scores after 3 years with/without 1:1 laptops. | Research Question 1: What is the effect of Technology Immersion on students’ learning opportunities (i.e., classroom activities, engagement)?
Research Question 2: Does Technology Immersion affect student achievement? | No hypothesis | N | 1 | 1 | 0 | Study 1 | 42 schools | L | 3 years | 1:1 technology program in the middle school versus no such program | They either had the program or they didn't | 5 | Y | NA | Y | 21 schools that did not have a new 1:1 technology program implemented | Y | RQ1: Survey data
RQ2: TAKS scores | Survey or state test | 4 | Y | N | No, but they did try to control external factors by matching a condition school with a control school based on similarity between the school/district | Y | N | Improve in TAKS scores not positive, but trending in right direction for long term improvement
Less behavioral issues | NA | NA | Y | By carefully matching schools to condition and control groups | Kind of | The study was done in impoverished communities in Texas, which is not representative of the entire middle school population | Y | | 6 | 8 | |
| Lydia | LF-001 X | 10/6/18 | Health | What are the effects of screen time on student well being? | Media and technology use predicts ill-being among children, preteens and teenagers independent of the negative health impacts of exercise and eating habits | Rosen, L.D. ; Lim, A.F. ; Felt, J. ; Carrier, L.M. ; Cheever, N.A. ; Lara-Ruiz, J.M. ; Mendoza, J.S. ; Rokkum, J. | Rosen, L., Lim, A., Felt, J., Carrier, L., Cheever, N., Lara-Ruiz, J., . . . Rokkum, J. (2014). Media and technology use predicts ill-being among children, preteens and teenagers independent of the negative health impacts of exercise and eating habits. Computers in Human Behavior, 35, 364-375. doi:10.1016/j.chb.2014.01.036 | doi:10.1016/j.chb.2014.01.036 | Q1 | 3.536 | 37 | Yes | This source evaluates the effects of screen time and media exposure on the health of children in four different realms (physical health, psychological issues, behavioral problems, and attention problems). | This study examined the impact of technology on four areas of ill-being— psychological issues, behavior problems, attention problems and physical health—among children (aged 4–8), preteens (9–12), and teenagers (13–18) by having 1030 parents complete an online, anonymous survey about their own and their child’s behaviors | Hypothesis 1. Unhealthy eating will predict ill-being even after factoring out parent and child demographics, and daily technology use. Hypothesis 2. Lack of physical activity will predict ill-being even after factoring out parent and child demographics, and daily technology use. Hypothesis 3. After factoring out both demographic data for parent and child, unhealthy eating, and lack of physical activity, media usage will predict ill-being. | N | 1 | 0 | 1 | Study 1 | 1030 | CS | NA | Eating habits, physical activity, and media use | Parents were asked a series of 10 questions concerning their daily media and technology usage (going online, using a computer for other than being online, sending and receiving e-mail, IMing/chatting, talking on the telephone, texting, playing video games, listening to music, and playing with technological toys) on a scale including: not at all, less than an hour, 1 h, 2 h, 3 h, 4–5 h, 6–8 h, 9–10 h and more than 10 h per day (Carrier, Cheever, Rosen, Benitez, & Chang, 2009). In addition, parents were asked about their child’s technology ownership (cell phone, iPod/MP3 player) and his/her use of technology in their bedroom (television, video games, computer, DVD player). Using the same scale as for media/technology usage, parents were asked about their child’s daily outdoor play or exercise in terms of hours per day. This single item was used to create a scale of physical activity. Parents were asked about food consumption for themselves and their child including: dairy products, water, diet drinks, regular soda, energy drinks, coffee, fruits/vegetables, whole grains and beans, eggs, seafood, chicken/turkey, pork, beef, junk food and sweets, fried food, fast food meals, vitamins, alcohol, and cigarettes on a 10-point scale ranging from never through seven or more times a day. A subset of these items was used to construct a scale of unhealthy eating. | 4 | Y | NA | N | NA | N | Child ill-being | Parents were asked questions concerning their health as well as their child’s health in four areas: Physical Health Symptomology (sick days in the last 12 months, general physical health, and two items—headaches and stomach aches—from an 11-item symptomology checklist developed by the experimenters. The survey also asked about behavior problems in three items from the 11-item symptomology checklist: difficulty making and keeping friends, behaviors, and anger or emotional outbursts. The survey included the 18-item Attention Deficit Hyperactivity Disorder Rating Scale–IV–school version (DuPaul et al., 1997) with each item answered on a four-point scale of never or rarely, sometimes, often and very often. Additionally, a parent and child attention symptomology checklist (e.g., antisocial behaviors, difficult paying attention) was included. The survey included several items including two from the 11-item symptomology checklist (depression, anxiety), a single question that queried the stress level on an average day (1 = not at all stressed to 10 = extremely stressed), the Yale Single Item Depression Scale which has been shown to be reliable and valid (Lachs et al., 1990) and the Rosenberg Self-Esteem Survey (Rosenberg, 1965). | 4 | Y | Y | Body-mass index, demographic data | N | N | Thus, overall, unhealthy eating did significantly predict ill-being for each age group although in some cases, this was moderated by technology use. Children’s health was strongly related to daily physical activity while for preteens physical activity predicted only behavior problems and for teenagers physical activity predicted all forms of ill-being other than attention problems. Thus, it appears that for children and preteens, overall technology use may be the culprit in ill-being, although for preteens some specific technologies—video games, cell phone, email, IM/chat, and technological toys—did predict ill-being in one form or another. For teenagers, however, it appears that the culprit in predicting ill-being of any type is primarily technology and that outside of behavior problems it appears that overuse of any technology significantly predicts ill-being. | Hypotheses 2 and 3 | Hypothesis 1 | Y | They controlled for other factors during each analysis and looked for mediating relationships. | Y | First, although it uses path analysis, which can be stretched to assume causality, it is really a simple correlational study. Second, the study has a statistical limitation in that so many inferential tests were computed at the .05 significance level that one in 20 would be expected to be significant by chance. Third, parents answered all questions for the children, preteens, and teenagers rather than having them answer on their own. There is no way to tell if the parents were inflating or minimizing any of their responses, particularly with respect to sensitive issues such as screen time and eating habits. | Y | Con: this study suggests that screen time is related to ill-being in children, preteens, and teenagers. This is particularly true of teenagers and could imply that additional technology in the classroom would be harmful to the overall well-being of students. | 9 | 7 | Y |
| Lydia | LF-002 | 10/6/18 | Health | Effects of screen time on health | Youth screen-time behaviour is associated with cardiovascular risk in young adulthood: The European Youth Heart Study. | Grøntved, Anders ; Ried-Larsen, Mathias ; Møller, Niels Christian ; Kristensen, Peter Lund ; Wedderkopp, Niels ; Froberg, Karsten ; Hu, Frank B ; Ekelund, Ulf ; Andersen, Lars B | Grøntved, A., Ried-Larsen, M., Møller, N. C., Kristensen, P. L., Wedderkopp, N., Froberg, K., . . . Andersen, L. B. (2012). Youth screen-time behaviour is associated with cardiovascular risk in young adulthood: The European Youth Heart Study. European Journal of Preventive Cardiology, 21(1), 49-56. doi:10.1177/2047487312454760 | doi:10.1177/2047487312454760 | Q1 | 4.542 | 36 | Yes | This source uses a prospective study to analyze the impact of screen time in youth and adolescence on cardiovascular disease risk factors in young adulthood. This is particularly of concern to American students, as the study found a connection in Dutch students and Americans have a uniquely high prevalence of cardiovascular disease. | We prospectively examined the association of TV viewing, computer use, and total screen time in adolescence, and change in these behaviours, with cardiovascular disease (CVD) risk factors in young adulthood. | NA | N | 1 | 0 | 1 | Study 1 | The eligible cohort for the current analyses was 435 individuals who had complete data on exposures and outcomes (244 individuals with 6-year follow up and 191 individuals with 12-year follow up). | L | 6 and 12 years | Television viewing, computer use, and total screen time | At baseline and follow up, TV viewing and computer use time during leisure was obtained by self-report. In both instances, this was done using a computer-based questionnaire | 4 | Y | NA | N | NA | N | Cardiovascular risk factors | Height, weight, and waist circumference (WC) were measured using standard anthropometric procedures. Fasting blood samples (overnight) were taken in the morning from the antecubital vein. | 4 | Y | N | NA | N | N | Prolonged TV viewing and total screen time in adolescence, and increases in screen time through young adulthood, were consistently associated with greater adiposity and clustered CVD risk in young adulthood. | NA | NA | Y | The associations were independent of various confounding factors, including objectively measured MVPA and showed evidence of dose–response relationships. | Kind Of | All screen time measures were self-reported and measurement errors are therefore inevitable. Loss to follow up and missing data can lead to bias if the associations are different in these individuals. We found differences in some baseline characteristics among individuals lost to follow up or with missing data compared with the individuals with complete data. In addition, our study was not adequately powered to consistently do stratified analyses by cohort, which could provide valuable information about the timing of interventions to prevent the large increase in viewing time. | Y | Con: this study concludes that there is a relationship between screen time, screen time increases, and cardiovascular disease risk factors. This study was down on Danish young adults, but reached the same conclusion as another cohort study in New Zealand, suggesting that these results may be generalizable. | 10 | 8 | Y |
| Blake | BP-005 | 10/8/18 | Educational Impact/Equity & Implementation | Assessing educational value of these devices | Assessing the educational value of one-to-one devices: have we been asking the right questions? | Davies, Chris &
Marte Blikstad-Balas | Marte Blikstad-Balas & Chris Davies (2017) Assessing the educational value of one-to-one devices: have we been asking the right questions?, Oxford Review of Education, 43:3, 311-331, DOI: 10.1080/03054985.2017.1305045 | 10.1080/03054985.2017.1305045 | Q1 | 1.393 | 3 | Don't know | Looks at how much students actually use devices and for what purposes they are used in the classroom. Also, a bit about teachers' feelings toward using such technology (a barrier in implementation) | how are these devices being used, what purposes are they serving, and in what ways are they proving beneficial? | NA | N | 4 | 0 | 0 | Study 1 | General analysis and observation of of nine classes in a single day, with 17 students agreeing to be interviewed | CS | NA | Investment in, and use of devices | The school paid the full cost of this initiative. Substantial preparation time was devoted to staff induction into the scheme, involving establishing clear agreed procedures and rules for the use of the machines in class and beyond, and exploring pedagogical applications. Students were expected to carry these devices (all of which had rubberised protective covers) with them at all times during school, to use them only on their teachers’ instructions and guidance, and to take them home each evening. | 3 | Y | NA | N | NA | N | benefits, both practical and educational. | Evaluations of five post-graduate students in classroom and interviews from willing students, along with administrative examination of measurable academic improvements | 4 | Y | N | NA | N | Y | It will be clear by now that we see the outcome of the second and major purpose of this paper—to probe the conceptions of educational value that are implied in the perspectives and assumptions surrounding one-to-one technologies—as revealing a lack of substantive educative engagement with the topic of technology itself. Useful and welcome as the convenience and utility of these technologies are in educational activities within school, we have not come across much evidence of their having transformed educational practices for the better, nor of their having enabled innovative approaches to teaching and learning which would not otherwise have been possible, nor—most importantly—do they appear to have been used in order to expand the scope and quality of students’ understanding of the world. For a variety of quite understandable reasons, schools prefer to adopt a largely functional relationship to the technologies that they buy (or encourage the parents of their pupils to buy), and do not engage very much with the more contentious or risk-laden aspects of the digital world. This is done, perhaps, in the hope of achieving an acceptable degree of consensus about the justifiability of these investments, in the face of doubts from many quarters concerning their more negative aspects.
They also pointed out that the technology was used to only supplement or compliment existing curriuclum, that different aged kids used it for different purposes, and that the overall purpose or benefit was largely convenience | NA | NA | N | NA | IDK | NA | Y | Con: despite the devices having a clear "convenience" factor in students' lives and the students finding them somewhat useful, the program was discontinued due to the lack of evidence supporting that the devices made a significant impact on the students' learning by school administration. | 9, very good at bringing up uncommon issues (more practical) that are not addressed in other studies, but these are not scientifically sound claims based on the fact that it was one school in England | 6 | N |
| Blake | BP-006 | 10/8/18 | implementation | What other "costs" exist when implementing a 1:1 program other than purchasing the physical devices | Teacher beliefs and technology integration practices: A critical relationship | Peggy A.Ertmera, Anne T.Ottenbreit-Leftwich, Olgun Sadik , Emine Sendurur, Polat Sendurur | COMPUTERS & EDUCATION
Volume: 59 Issue: 2 Pages: 423-435
DOI: 10.1016/j.compedu.2012.02.001
Published:SEP 2012 | | Q1 | 5.438 | 259 | yes | This sources looks at the beliefs teachers hold about technology and its use in the classroom as a major barrier to assess when implementing a technology program even if other "First order" barriers are eliminated or reduced. Will be useful is other side argues barriers are too easy to overcome to be a true CON argument. | 1) How do the pedagogical beliefs and classroom technology practices of teachers, recognized for their technology uses, align? How do the pedagogical beliefs and classroom technology practices of teachers, recognized for their technology uses, align?
2)
To what extent do external, or first-order, barriers constrain teachers’ integration efforts, leading to potential misalignment between beliefs and practices? | NA | N | 1 | 0 | 1 | Study 1 | 12 | CS | NA | Pedagogical beliefs of teachers, perceived barriers | interviews and on a 1-5 scales | 5 | Y | Teachers were asked to identify the severity of each barrier on the scale but then also asked the biggest barrier of all which did not quite align with their personal rankings on the scale | N | NA | N | Integration of technology in the classroom | Analyses of teacher websites looked at 1) the extent to which students, rather than teachers, used the technology, 2) the level of interactivity (with content, teacher, and peers) and collaboration evident, 3) the types of homework assignments students were asked to complete, 4) the resources and web links teachers provided for their students, and 5) the types of assessments used. Also interview data asking about lesson plans, etc. | 4 | IDK | Y | Biggest barrier overall and also the comparison between teachers' beliefs internally as opposed to external barriers | N | N | Even among award-winning teachers, barriers such as a lack of resources, lack of administrative support, technology problems, and standardized tests are still considered issues by some. This is similar to what Becker (1994) observed over 15 years ago: even among exemplary users, barriers are known to exist. Yet, 11 of the 12 teachers in this study were able to enact practices that closely aligned with their beliefs, suggesting that second-order, not first-order, barriers are most impactful | NA | NA | Y | Examined three potential areas on concern that led to their results which contradicted previous reserach. These areas are as follows: change in access; change in students; change in curricular emphases. Compared results to other studies and attempted to explain their results compared to others. | Kind of | Given the relatively small number of participants in this study, results are not readily generalizable. In order to verify these results, a larger sample is needed. In addition, teachers in this study were selected based on their high levels of technology use, thus providing little insight into how beliefs and practices align for teachers at the lower levels of use or for those who are in transition. Our one discrepant case suggests that beliefs change before practice and that practices may be limited by first-order barriers, especially if beliefs are peripheral, or in transition. However additional cases are needed to support this conclusion. Finally, in this study teachers’ practices were not directly observed, but rather inferred from their websites and descriptions of practice, provided during interviews. Observations would provide a richer understanding of enacted beliefs. | Y | Both: describes that certain barriers can be overcome by teachers if their pedagogical beliefs allow for them to do so. However, also discusses the difference between first and second- order barriers (internal and external) and how not every teacher may implement technology even if certain barriers are eliminated. | 9 | 7 | Y |
| Sam | SM-001 | 10-08-18 | Importance of digital competency | what are the numbers for technology use? Why is it important to be digitally competent? | CONTEMPORARY DIGITAL COMPETENCY REVIEW | Zoltán Nyikes | INTERDISCIPLINARY DESCRIPTION OF COMPLEX SYSTEMS
Volume: 16 Issue: 1 Pages: 124-131
Published:2018
Document Type:Review | DOI: 10.7906/indecs.16.1.9 | not on the page... | not on the page... | 1 | Don't know | in the abscence of any good sources about how technology in education help kids in the future. I found this review giving the numbers about technology use. Tells and supports the importance of digital competency in the world today. | | NA | Y | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Both- this shows some of the dangers of internet use. Should we teach kids about the dangers with use of tech or protect them by limiting access? | 7 | Review paper | N |
| Sam | SM-002 X | 10-09-18 | Importance of digital competency | How is digital literacy important? How can it help the kids who have this competency? | Digital Reading Competency of Students: A Study in Universities in Kerala | Divya P. and Mohamed Haneefa K.* | DESIDOC JOURNAL OF LIBRARY & INFORMATION TECHNOLOGY
Volume: 38 Issue: 2 Pages: 88-94
Published:MAR 2018
Document Type:Article | DOI: 10.14429/djlit.38.2.12233
| not on the page... | not on the page... | 0 | Don't know | The article studies the competency of boys and girls at some universities in India and shows that familiarity and comfort with reading online sources improved online information gathering speeds and understanding. | R1: How does confidence in digital reading effect other aspects of information gathering? R2: Does digital confidence effect retintion and linking of knowledge gained? | NA | N | 1 | 0 | 1 | 1 | 426 | CS | NA | Years of experience with computers | Years | 5 | Y | None | N | NA | N | Digital Reading competency | % of the sample able to perform the task | 4 | Y | Y | Gender of the participants | N | N | Years of technology experience was a very good predictor of digital competency | NA | NA | N | NA | Y | none... | Y | Pro- This paper briefly outlines the importance of digital competencies and shows how exposure to technology is correlated to increased digital reading competency. | 8 | 7 | Y |
| Colin | CB-003 | 10-09-18 | Educational Equity | Is there still a first level divide in access to computers/internet? | Revisiting the First-Level Digital Divide in the United States: Gender and Race/Ethnicity Patterns, 2007-2012 | Campos-Castillo, C. | Campos-Castillo, C. Revisiting the First-Level Digital Divide in the United States: Gender and Race/Ethnicity Patterns, 2007-2012. Social Science Computer Review, 33, 423-439 (2015). | 10.1177/0894439314547617 | Q1 | 3.253 | 5 | Yes | There is still evidence of a first-order digital divide. This article presents somewhat contemporary data, which is useful because a lot of recent literature has started to focus on the second-order divide since technology has become so ubiquitous. | Research Question 1: Do racial and ethnic minorities (Blacks and Latina/os) have lower Internet access than Whites?
Research Question 2: How does the Internet access among Latina/os compare to Blacks?
Research Question 3: Do women have greater Internet access than men?
Research Question 4: Do gendered patterns of Internet access differ by race/ethnicity? | NA | N | 1 | 0 | 1 | Study 1 | 8,412 | CS | NA | Race, gender | Survey | 5 | Y | The sample size reported is after removing incomplete responses | N | NA | N | Internet access | The survey question "Do you ever go on-line to access the Internet or World Wide Web, or to send and receive e-mail? (yes/no)." | 5 | Y | Y | From the text:
"I selected controls based on prior research on demographic characteristics that shape Internet access [citations]. These included immigrant status, homeownership status, living in an urban versus rural area, education level, age (years), employment status, annual household income, and marital status. In a preliminary analysis, I compared a linear to a curvilinear approximation of the relationship between age and access and found that the linear approximation fitted these data better." | N | N | RQ1: "In 2007, Black and Latino respondents were significantly less likely to report having access to
the Internet than White respondents, mirroring results obtained from 2008 [citations]. Both the Black-White and Latino-White differences narrow in 2012, but notably remained statistically significant. This shows that a racial and ethnic divide in Internet access
that favors Whites was still present in 2012."
RQ2: "... not only is Internet access comparable between Blacks and Latinos, but the gains among this group from 2007 to 2012 are also comparable."
RQ3: "In other words, women were significantly more likely than men to report having access in 2007 and this gap did not change much in 2012. Both of these findings are consistent with an assessment of the gender divide from 2002 to 2008 [citation]."
RQ4: "... the analyses of the intersections between gender and race and ethnicity showed that in 2012, the gender divide only appeared among Whites and that Black men are the newest Internet users." | NA | NA | Y | He correlated internet access with the alternative variables identified in cell AL to make sure there were not underlying trends based on these factors that alter the interpretation of the results. | Y | The sample size is too small to analyze internet access for all ethnic groups in the U.S.
Differences in the 2007 and 2012 survey respondents cloud the results, but the author argues that these differences based on the year the survey was taken accentuate the differences in internet access amongst groups. | Y | Con- There is still evidence that some groups have disproportionately less access to the internet. A 1:1 program that shifts learning onto the computer might further disadvantage these children. | 5 | 7 | Y |
| Colin | CB-004 | 10/9/18 | Educational Equity | Review of data on digital divides in U.S. K-12 schools | Splicing the Divide: A Review of Research on the Evolving Digital Divide Amongst K-12 Students | Dolan, J. E. | Dolan, J. E. Splicing the Divide: A Review of Research on the Evolving Digital Divide Amongst K-12 Students. Journal of Research on Technology in Education 48, 16-37, (2016). | 10.1080/15391523.2015.1103147 | Not indexed | Not indexed | 13 | Yes | This review article surveys literature on the digital divide in K-12 U.S. schools. The latter distinction is important because a fair amount of the research in this area is from Scandinavian countries. I think this is a good article for the legal team to get reliable statistics from, and is valuable for its list of cited articles. | In what ways has the digital divide evolved as technology is integrated into K–12 schools? What factors in and out of schools support or constrain K–12 students with regard to technology use? | NA | Y | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| Lydia | LF-003 | 10/11/18 | Health | Effect of screen time on health | Associations of Cardiorespiratory Fitness in Children and Adolescents With Physical Activity, Active Commuting to School, and Screen Time | Aires, L. ; Pratt, M. ; Lobelo, F. ; Santos, R.M. ; Santos, M.P. ; Mota, J | Aires, L., Pratt, M., Lobelo, F., Santos, R. M., Santos, M. P., & Mota, J. (2011). Associations of Cardiorespiratory Fitness in Children and Adolescents With Physical Activity, Active Commuting to School, and Screen Time. Journal of Physical Activity and Health, 8(S2). doi:10.1123/jpah.8.s2.s198 | doi:10.1123/jpah.8.s2.s198 | Q2 | 1.723 | 17 | Yes | This study investigates the relationships between cardiorespiratory health and physical activity, active commuting to school, and screen team among middle and high schoolers. The results could inform predictions on the potential health impact of 1:1 technology on this age group. | The purpose of this study was to investigate whether physical activity levels, time spent watching television or using computer, mode of commuting to school and adiposity were independently associated with levels of CRF in girls and boys aged 11 to 19 years. | NA | N | 1 | 0 | 1 | Study 1 | 1708 students | CS | NA | Physical activity, active commuting, and screen time on the television or computer | Physical activity was assessed by a questionnaire that was previously determined to have good reliability. Participants were asked how they do commute home/school (by car, bus, train, bicycle, or walking), and how much time it took. We measured time watching television (TV time) and using computer (PC time) with a questionnaire. Participants were asked how many hours and minutes they usually watched television or used a computer for work or leisure during the day preceding the examination (to measure weekday usage) as well as during the weekend | 4 | Y | NA | N | NA | N | Bodymass and cardiorespiratory fitness | Body mass was measured to the nearest 0.1 kg with an electronic weight scale (Tanita Inner Scan BC 532) with subjects in t-shirts and shorts. Body mass index (BMI) was calculated from the ratio weight/height^ (Kg-m"^). Participants were required to run back and forth between 2 lines 20 meters apart starting at 8.5 km h"'' with speed increasing by 0.5 km-h"' each minute. Subjects were instructed to run in a straight line, pivot, and turn on completing a shuttle, and to pace themselves in accordance with audio signals. The test was finished when participants stopped due to fatigue or when they failed to reach the lines concurrent with the audio signals on 2 consecutive occasions. The total number of completed laps was recorded and then transformed into a V02max by previously determined equation. | 5 | Y | Y | Socioeconomic status and maturation stage | N | N | CRF was independent and positively associated with physical activity and with maturation; independent and negatively associated with television time and adiposity. CRF was positively associated with CS. No associations were found for computer time | NA | NA | Y | Authors controlled for each factor independently | Kind Of | The study was limited in sample size and provides only cross-sectional data from 2 schools, which makes it difficult to generalize these findings. The self-reported nature of the data for physical activity, or sedentary behavior is also a limitation and may bias results. | Y | Both: Cardiorespiratory health was negatively associated with time spent watching TV, but not with time spent on the computer | 7 | 8 | Y |
| Lydia | LF-004 | 10/11/18 | Health | Effect of screen time and physical activity on retinal microvasculature in children | Influence of Physical Activity and Screen Time on the Retinal Microvasculature in Young Children | Gopinath, Bamini; Baur, Louise A.; Wang, Jie Jin; Hardy, Louise L.; Teber, Erdahl; Kifley, Annette; Wong, Tien Y.; Mitchell, Paul | Arteriosclerosis Thrombosis and Vascular Biology, Volume: 31, Issue: 5, Pages: 1233-1239, 2011 | 10.1161/ATVBAHA.110.219451 | Q1 | 6.086 | 28 | Yes | This is a great paper that shows how screen time effects sight and eye health of children | We aimed to assess associations among physical activity levels (indoor and outdoor activities), a range of indicators of sedentariness (screen time, TV viewing, computer and video game usage, and reading), and retinal vascular caliber during middle childhood. | NA | N | 1 | 0 | 1 | Study 1 | 1492 6 year olds | CS | NA | Time spent on physical vs sedentary activities | Parents were asked to report the number of hours per week their child spent in each of these activities and whether the activity was done out doors or indoors (hall gym, classroom). The time spent in each activity was summed, and the average hours per day spent were calculated separately for outdoor activities, indoor activities, and total activity time (ie, sum of outdoor and indoor activities). Total screen time (hours per day) was calculated as the time reported that was spent on the following activities: watching TV, using video games, and computer usage (which included using the computer for games and for homework). | 4 | Y | NA | N | NA | N | Retinal vascular caliber | Children’s eyes were dilated, and digital photographs were taken of the optic disc and macula of both eyes using a Canon 60UVID10 fundus camera. One grader, masked to participant identity and characteristics, measured retinal vessel caliber using a computer-assisted program with high reproducibility, as has been previously described. Average retinal arteriolar and venular calibers were calculated using the Knudtson-Hubbard formula | 5 | Y | Y | Weight, body fat, and height | N | N | Our findings that school children engaging in higher levels of physical activity have a better retinal vascular caliber profile (wider retinal arterioles), whereas those spending increased time in screen time have a more adverse retinal microvascular profile (narrower arterioles), suggests that lifestyle factors may influence the microcirculation early in life. | NA | NA | Y | They controlled for other factors and used a mixed random sample of students around Sydney | Kind Of | A limitation was the use of parent proxy report rather than an objective measurement of time spent in physical and sedentary activities. A second limitation is that the study design is cross-sectional and does not provide temporal information on the associations. Third, we cannot exclude the possibility of residual confounding, although we have attempted to adjust for several confounders | Y | Con:increased screen time seems to be associated with worse retinal vascular caliber outcomes in children | 7 | 8 | Y |
| Colin | CB-005 | 10/14/18 | Educational Impact (Substantial Learning) | Propensity of students to use verbal vs. spatial note-taking strategies when working on laptops as compared to pen/paper or whiteboard | Spontaneous Spatial Strategy Use in Learning from Scientific Text | Fiorella, L. and Mayer, R. E. | Fiorella, L. and Mayer, R. E. Spontaneous Spatial Strategy Use in Learning from Scientific Text. Contemporary Educational Psychology, 49, 66-79 (2017). | 10.1016/j.cedpsych.2017.01.002 | Q1 | 3.356 | 1 | Yes | This article asks the interesting question of how different note-taking strategies influence the frequency with which students use different learning strategies. While it is interesting research, I think the sample size is too small and the conclusions too speculative to be the bed of a strong SciCourt argument. | "The purpose of Study 2 was to experimentally test whether different note-taking environments cause students to spontaneously choose different learning strategies. Previous research comparing note-taking media (e.g., computer vs. hand-written notes) has focused on the use of verbal strategies and its effects on learning outcomes, showing somewhat mixed results [citations]." | The researchers hypothesize that there will be a difference in note-taking strategy based on the medium used to record notes. Specifically, they think paper/whiteboard note-taking will lead to statistically significant increases in visual note-taking vs verbal note-taking. | N | 2 | 2 | 0 | Study 2 | 94 undergraduate students | CS | NA | Note-taking medium | Students either took notes on paper, on a whiteboard, or on a laptop | 5 | Y | NA | N | NA | Y | Effectiveness of note-taking strategy in learning lecture information | A post-test with 8 questions: 1 about retention, 5 about transfer, and 2 about drawing. | 4 | Y | N | Age, gender, spatial ability, prior knowledge of the subject | N | N | Computer note-takers did use more verbal note-taking strategies at a statistically signficant level as compared to paper and whiteboard note-takers. There was no significant difference between the paper and whiteboard groups in terms of strategy employed.
The computer note-takers outperformed both the paper and whiteboard groups on the post-test, despite using fewer visual note-taking strategies. | The one listed on this document | NA | Y | They demonstrated in the case of gender, spatial ability, and prior knowledge that the 3 groups were homogeneous. There was a statistically larger mean age for the paper note-taking group, but analysis of performance against age shows that this age is not correlated with performance. | Kind Of | Coding of strategies was only done based on an attempt to use a structure, and not on how complex or insightful that structure is (i.e. the student drew a flow chart, but it is poorly done and is missing key connections)
The sample size is very small
"Further research should address additional factors that might influence or covary with students’ strategy use and learning outcomes, such as prior knowledge, motivation, beliefs about learning, or self-regulation ability. Exploring these potential covariates is especially important given that strategy use was spontaneous in
the present study, and thus does not allow causal inferences linking strategy use and learning outcomes" | Y | Both:
- Con: Paper notes promote more spatial note-taking, which can often be beneficial
- Pro: The computer note-takers, despite sticking mostly to verbal note-taking, performed better than the paper/whiteboard note-takers | 3 | 6 | N |
| Colin | CB-006 | 10/14/18 | Educational Impact (Substantial Learning) | Effectiveness of paper vs computer notes | Note-Taking with Computers: Exploring Alternative Strategies for Improved Recall | Bui, D. C., Myerson, J. and Hale, S. | Bui, D. C., Myerson, J. and Hale. S. Note-Taking with Computers: Exploring Alternative Strategies for Improved Recall | 10.1037/a0030367 | Q1 | 4.433 | 36 | Yes | It is seen as somewhat common knowledge that handwritten notes are more effective than computer notes. This article examines the issue again, but with 3 distinct experiments that allow them to explore different variables such as working memory. They find that computer notes in which the student tries to transcribe as much of the lecture as possible have distinct benefits. | How does taking notes on a computer versus by hand affect how students learn from and retain information from lectures? | The researchers hypothesize that taking notes by computer will benefit students with lower working memory because it is faster.
Taking more notes may lead to more learning (organization vs transcription) | N | 3 | 3 | 0 | All 3 | 80, 76, and 72 undergraduate students | CS | NA | Note-taking medium, note-taking strategy | 2x2 study: Participants were either instructed to transcribe a lecture or write down as organized of notes as possible. They were also either given a pen and paper or a compute with Microsoft Word. | 4 | Y | NA | N | NA | Not explicitly stated, but I'm fairly certain they were | Effectiveness of note-taking strategy in learning lecture information | A free recall test (asked to write down as much as they could remember from the lecture) and a short-answer test | 4 | Y | Y | Proportion of idea units to overall notes (to determine whether or not participants had followed the instructions to transcribe or organize) | Y | Y | Suggest that the use of computers for transcribing lecture notes allows students with low working memory to generate more information, increasing performance on a test that requires information recall (Experiment 3). This benefit only persists over a 24 hr. period if students are allowed to study these notes after the lecture (Experiment 2). In the case that they are not allowed to study notes after the lecture, organized notes are more effective for retention over a 24 hr. period (Experiment 2). Transcribed notes are better for immediate recall post-lecture (Experiment 1). | Both hypotheses listed were supported to some extent | NA | Y | They measured working memory and speed of processing for all participants before the study. | Kind Of | Not sure if the results transfer to tests that require a stronger conceptual understanding of the material
Obviously, students must be able to type well
The lecture was only 11 min, so studies need to be done to see how well the trends transfer to longer lectures or e-Learning environments | Y | Pro: This is an example of how computer access can benefit students with different skillsets (low working memory) | 5 | 7 | Y |
| Blake | BP-007 | 10/15/18 | Attitude and Beliefs (Second order barrier) | Do teachers' personal technology beliefs/teaching beliefs affect integration of technology? | The role of value on teachers' internalization of external barriers and externalization of personal beliefs for classroom technology integration | Vanessa W. Vongkulluksn, Kui Xie, Margaret A. Bowmana | COMPUTERS & EDUCATION
Volume: 118 Pages: 70-81
DOI: 10.1016/j.compedu.2017.11.009
Published:MAR 2018 | 10.1016/j.compedu.2017.11.009 | Q1 | 4.538 | 3 | Yes | This study is specifically investigating teachers' beliefs and the roles they play in integrating technology and receiving support on first-order barriers from the school/administrators. Includes a large sample size from the Midwest, perhaps making it more releveant to our case. | 1. How does actual school support affect teachers' perceived support on first-order barriers (internalization process)? How is this relationship influenced by teachers' value beliefs?
2.
How does teachers' perceived support on first-order barriers affect their classroom technology integration practice (externalization process)? How is this relationship influenced by teachers' value beliefs? | For the internalization pathway, we hypothesized that value beliefs mediate the relationship between actual school support and perceived support on first-order barriers (pathway #1). That is, actual school support may have a partial indirect effect on perceived support through the value beliefs variable. We also hypothesized that value beliefs may function as a moderator that influences how actual school support is related to perceived support on first-order barriers (pathway #2). For teachers who hold high levels of value beliefs for technology, an increase in actual school support may translate to a higher increase in their perceived support compared to those with lower levels of value beliefs. In addition, we hypothesized that actual school support would have an overall positive effect on perceived support on first-order barriers (internalization process). | N | 2 | 0 | 2 | 1 | The sample for this study was 624 sixth-to twelfth-grade teachers and 20 administrators from 16 schools across a Midwestern state in the United States. There were 365 female and 259 male teachers. Of these, 157 teachers held a Bachelor's degree, 461 held a Master's degree, and 6 held a doctorate degree. The average teacher had about 13 years of teaching experience and about 24 students in his/her classroom. | CS | NA | actual school support specified as the independent variable, value beliefs as the mediator | actual school support: 11, 5-point scales. Value beliefs: 3-item value beliefs survey | 4 | Y | NA | N | NA | N | perceived support on first-order barriers | 14 item survey, 5 point scale | 4 | Y | Y | Teaching experience, technology integration, ability beliefs (of teachers) | Y | Y | value beliefs had a direct association with teachers' technology integration practice. Teachers who believed that technology would enhance their teaching spent more time in the classroom using technology. In fact, we found that value beliefs were a stronger predictor of integration quantity than teachers' ability beliefs for technology use. In addition, teachers' value beliefs also predicted how well teachers integrated technology, including how much they used technology to foster student-centered instruction and higher order tasks. Teachers who believe that technology is valuable in the classroom tend to amplify the access they have and place less weight on access constraints when they make judgments about how much external barriers exist in their school context. | Both hypotheses listed were supported to some extent | NA | Y | Tried to eliminate bias associated with self-reported data by verifying it through multiple survey types and by "checking" the teachers' responses with administrators and technology specialists for accuracy/honesty. | Y | This study has limitations that stem from certain logistic and contextual constraints. The first limitation is a result of the use of self-report surveys, particularly for our technology integration indices. We were not offered the opportunity to observe classrooms or interview teachers, which would have provided more objective measures of classroom technology integration. As such, our results may be skewed due to the self-report bias that is present when subjects are asked to report their own behaviors (Greene, 2015). Although we noted that self-report surveys are typically used in studies referencing the Barriers to Technology model (e.g. Hixon and Buckenmeyer, 2009, Kopcha, 2012, Miranda and Russell, 2012, Mueller et al., 2008), we endeavored to minimize this bias through collecting multiple types of survey data. This includes asking teachers to assess the percentage of classroom time for which they integrate technology, complete a checklist of the types of instructional practice for which they use technology, and use Likert-scale measures to indicate perceptions that could not be tapped otherwise. In order to avoid the sole use of teachers' self-reported perceptions, we also sourced data from school administrators and technology specialists. They provided us with more objective measures of technology access, including the number of devices available in each school. Relatedly, another limitation of the study is a consequence of using quantitative measures to explain the complex phenomenon of technology integration. Again, teachers' qualitative narratives would have bolstered our understanding of technology integration in each specific classroom. However, our aim is to empirically corroborate the qualitative accounts of the role of value beliefs as documented in previous studies, and the use of quantitative methods is appropriate for this purpose. Our study also followed a clear theoretical model, which delineated relationships among different belief and behavior variables. As such, we could reasonably use the deductive, quantitative approach to answer our research questions instead of more inductive, qualitative methods. | Y | Neither, study simply outlines that the quality and quantity of proper technology integration is largely affected not only by well-known first-order barriers, but also second-order barriers, specifically realted to the beliefs of teachers. Outlines that these must be addressed or recgonized when looking to implement technology on a larger scale into classrooms. | 10 | 9 | Y |
| Daniel | DM-001 | 10/15/18 | Implementation: Professional Development | How important is teacher develpment to the implementation process? | High Access and Low Use of Technologies
in High School Classrooms: Explaining an
Apparent Paradox | Cuban, L; Kirkpatrick, H; Peck, C | Journal : American Educational Research Journal; Volume 38; Issue 4; Pages 813-834 | 10.3102/00028312038004813 | Q1 | 2.462 | 350 | Yes | It is a well cited study that inteviews teachers and students on the technological implementation at two technologically rich californian schools. | (1) With abundant access to information technologies, did the national patterns of
infrequent and limited teacher usage of computers emerge at the two high
schools? If so, why? (2) Did teachers in the two high schools who used
computers in their classrooms for instruction typically maintain existing practices?
If so, why? | NA | N | 2 | 0 | 2 | 1 | 21 Teachers and 26 students split between two schools | CS | NA | General acess to technology across the school. | Percentages of students and teachers that had computers at home, the frequency of computer usage among students and teachers, the types of computer use by students and teachers, and the ferequency of media lab usage among teachers. This data was collected with surveys sent out to students and teachers, as well as interviews with students and teachers. | 4 | Y | NA | N | NA | NA | How often teachers change their curriculum given the abundance of technology in schools | Teachers were interviewed and asked about whether, as well as how, they had changed their curriculum to incorporate more technology. | 4 | Y | N | NA | Y | Y | The data gathered from both schools confirm at least two of the reasons
commonly offered for limited and infrequent computer use in classrooms
High Access and Low Use of Technologies
and maintenance of teacher-centered instructional practices. First, teachers
do not have the time to find and evaluate software. Second, computer and
software training was seldom offered at convenient times. | NA | NA | N | NA | Kind of | None were listed. | Y | Neither, this source demonstrates that it is difficult to get teachers to use new technology, but also that it can strongly benefit at least some students. | 5 | 6 | N |
| Daniel | DM-002 | 10/15/18 | Implementation: Professional Development | How important is teacher develpment to the implementation process? | Identifying discriminating variables between teachers who
fully integrate computers and teachers with limited integration | Mueller, J; Wood, E; Willoughby, T; Ross, C; Specht, J; | Journal : Computers and Education; Volume 51; Issue 4; Pages 1523-1537 | 10.1016/j.compedu.2008.02.003 | Q1 | 4.538 | 152 | Yes | It is a relevant and detailed study of what makes a teacher able to sucessfully integrate technology. | The purpose of the current study was to survey in-service teachers who did, and did not integrate computers
in their classrooms, in order to identify the variables that best discriminated between these two groups at both
the elementary and secondary school levels. | NA | N | 1 | 0 | 1 | 1 | 185 Elementary Teachers, 204 secondary Teachers | CS | NA | Comfort with computers, computer use, computer training, attitudes toward computers, experiences with computer technology, teaching philosophy, teacher efficacy, attitudes toward work, computer integration | Each participant was asked to complete one survey. Two versions of the survey were developed (one
elementary and one secondary). The versions were identical in content except for questions relating to current
teaching assignments. The survey was developed based on the responses from educators in an earlier
focus group study with elementary and secondary teachers (Wood et al., 2005). Face validity of computerrelated
measures was ensured through the use of participants’ actual language for specific items describing
computer technology issues. The survey included a comprehensive set of measures addressing both computer-
related and general constructs. Computer-related constructs included computer integration, comfort
with computers, type of computer use, computer training, attitudes towards computers, and experiences
with computer technology. General constructs included demographics, teacher-efficacy, teaching philosophy,
and attitudes toward work. Brief descriptions of questions used to measure each construct are
included below.
Single-item questions were used to assess demographic variables including participant gender and years of
teaching experience. | 5 | Y | NA | N | NA | NA | There arent really output variables. The reasearchers are using an algorithm to categorize teachers into high and low integrator groups, then looking at which variables had the strongest impact on seperating the teachers into the two groups. "The purpose of the current study was to identify the variables that discriminate between in-service elementary
and secondary teachers who do, and those who do not, integrate computers in their classrooms. ‘‘Low”
and ‘‘high” integrator groups were created using the mean overall integration scores." | To examine which individual characteristics best discriminate between teachers who integrate computer
technology and those who do not, all study variables were simultaneously entered into a discriminant function
analysis (DFA) for both the elementary and secondary school levels. DFA can be thought of as the opposite of
MANOVA (Sprinthall, 2000). Rather than comparing scores on dependent variables for significant differences,
scores on study variables are used to predict group membership. Unlike the univariate analysis,
DFA provides an estimate of the relative importance of each of the study measures to the separation between
the two teacher groups when examined simultaneously | 5 | Y | N | NA | Y | Y | Our results clearly implicate both experience with computer technology and attitudes toward technology in
the classroom as important variables that predict differences between teachers who successfully integrated
computer technology from those who did not. Of the six variables that predicted integration among elementary
school teachers, four were related to computer-related experience. Similarly, of the four variables that
predicted integration among the secondary school teachers, three involved computer-related experience. These
outcomes support opinions, expectations and previous research findings presented in the literature (Becker,
1994; Foon Hew & Brush, 2007; Hadley & Sheingold, 1993; Rosen & Maguire, 1990; Wood et al., 2005). Specifically,
consistent with previous research, computer experience variables such as comfort with technology
and higher frequency of use of computers were significant contributors to the function that separated successful
elementary and secondary integrating teachers from their non-integrating peers. In addition, training with
computers was important at the elementary level. Our results, however, suggest that ‘‘general” exposure and
use is less critical than very specific, task-relevant, and classroom-applicable experience. Specifically, the positive
outcomes measure contributed the most to the discriminating function for both elementary and secondary
teachers. | NA | NA | N | NA | Yes | Study size; they didnt have enough teachers in individual disciplines in order to draw any conclusions about computer integration differences between disciplines. | Y | Neither, This source shows that teachers who are effectave at integrating technology have expereince with it or training with it. | 8 | 10 | Y |
| Daniel | DM-003 | 10/16/18 | Implementation: Professional Development | How important is teacher develpment to the implementation process? | Teachers’ perceptions of the barriers to technology integration and practices with
technology under situated professional development | Kopcha, TJ | Journal : Computers and Education; Volume 59; Issue 4; Pages 1109-1121 | 10.1016/j.compedu.2012.05.014 | Q1 | 4.538 | 70 | Yes | This is a longitudnal study on the efficacy of professional development on the implementation of technology in classrooms. | 1. How do teachers perceive the common barriers to technology integration after engaging in a program of situated professional
development over a two-year period?
2. How do those perceptions change as teachers’ professional development transitions from full-time mentoring to teacher-led
communities of practice?
3. What were teachers’ instructional practices under teacher-led communities of practice and how do they relate to their perceptions of
the barriers? | NA | N | 2 | 0 | 2 | Study 1 | 18 elementary teachers | L | 2 years | Teachers were transitioned from professional deveopment with a mentor to communities of practice without a mentor. | Teachers completed the survey in the fall of Year 2, reporting their perceptions of the common barriers from the previous year (Year 1).
Teacher-led communities of practice were established with support from the mentor until January of Year 2, at which time all external
mentoring ceased. In April and May of Year 2, teachers were videotaped delivering lessons that used technology as part of the lesson.
Videotaped lessons were recorded from two different perspectives: a fixed and a traveling position. The fixed position provided the
observers with a view of the entire classroom while the traveling position provided close-up screen shots of each student’s computer and
teacher–student and student–student interaction. Videotaping from two perspectives allowed the researcher to conduct a more focused and
deeper content analysis at a future time. In May of Year 2, participants completed the survey a second time (now referring to Year 2) and
were interviewed. Interviews lasted an average of 35 min. | 4 | Y | NA | N | NA | NA | The dependant variables are shown in Table 2 of the study. They are the average response from teachers to each of 15 questions. | The researcher created a survey to examine teacher perceptions of the common barriers to technology integration. Survey items were
rated using a standard five-point Likert-type scale ranging from strongly agree (4) to strongly disagree (0). The 15-items in the survey (3
items per barrier) were based heavily on Clark’s (2006) Delphi study | 4 | Y | N | NA | Y | Y | that the communities of practice in this study did not
substantially provide support or influence teachers’ professional learning during Year 2. Of the eight items that had lower ratings in Year 2,
five were from the barriers of professional development and time. Interviewed teachers similarly reported that it was more difficult to learn
to integrate technology or find time to share and locate resources without the mentor. While communities of practice are promoted as a cost-effective alternative to mentoring, this case suggests that not all communities of
practice can or will contribute to positive teacher outcomes when learning to integrate technology. It seems that the specific activities that
occur as part of or even prior to establishing a community of practice may play a larger role in promoting changes in teacher attitudes and
practices with technology. | NA | NA | N | NA | N | Both survey and interview data suggest that teachers’ beliefs about technology were initially quite strong. Since teachers with strong
beliefs are more likely to persist in their attempts to integrate technology (Ertmer & Ottenbreit-Leftwich, 2010; Ottenbreit-Leftwich et al.,
2010; Vannatta & Fordham, 2004), it is difficult to assess the influence of participant’s beliefs on the results of this study. In addition, the
context is unique – professional development at this schoolwas initiated in conjunction with a substantial technology upgrade and followed
a particular model of technology integration. The mentor who developed the professional development at this school was also a researcher
in the study. These issues, when combined with the small number of participants, make it difficult to determine whether the results would
be the same among teachers with different beliefs or in a school with different initial circumstances. | Y | Con: This study demonstrates that it is difficult for teachers to integrate technology unless there is a mentor to guide them for at least two years. | 7 | 7 | Y |
| Samantha | SV-001 | 10/16/18 | Educational Equity | How does availability of, access to, and use of new technologies in a group of low– and high–socioeconomic status (SES) California high schools impact students differently? | Technology and Equity in Schooling: Deconstructing the Digital Divide | MARK WARSCHAUER, MICHELE KNOBEL, and LEEANN STONE | Warschauer, Mark, Knobel, Michele, Stone, Leeann. Technology and Equity in Schooling: Deconstructing the Digital Divide. Educational Policy, Vol 18, Issue 4, pp. 562-588. Published September 1, 2004. https://doi.org/10.1177/0895904804266469 | 10.1177/0895904804266469 | Q2 | 1.586 | 110 | Yes | This article looks at the impacts of technology implementaiton in high schools of varying socioeconomic statuses and compares of the existing school conditions on students' success. | The study sought to investigate the availability of, access to, and use of new technologies within selected California public high schools, and the variation among these dimensions by school, community, and student population in relation to students’academic preparation for entry into universities. | On one hand, if computers and the Internet are distributed equally and used well, they are viewed as powerful tools to increase learning among marginalized students and provide greater access to a broader information society. On the other hand, many fear that unequal access to new technologies, both at school and at home, will serve to heighten educational and social stratification, thereby creating a new digital divide | N | 1 | 0 | 1 | 1 | 5 low-SES schools and 3 high-SES schools, 64 total teachers and their classes, broken down with a minimum of 4 teachers from each of the 8 schools, one from each core subject area | CS | NA | SES status and technology use in schools | SES status was measured by the percentage of the student population on free-and-reduced lunch, and within the domain of techonology use, teachers were interviewed and categorized by whether teachers presented themselves as active users, passive users, or users beset by constraints. | 3 | Y | NA | N | NA | NA | Academic preparation: this includes student mastery of a range of computer skills and software applications, being able to conduct effective Internet-based research, being familiar with working in educational contexts, and enrolling in appropriate classes | Transcripts of interviews with teachers were independently reviewed by two researchers and they constructed domain analyses and applied taxonomic analysis to the items within the domains to show relationships between included terms within a domain. When like terms were analyzed using different data sets (e.g., academic preparation, technology use), taxonomies greatly facilitated comparisons across our data. | 4 | Y | Y | Collected artifacts and texts related to technology policy and use in each school. These documents included technology policies, school-conducted technology inventories and surveys, school technology grant proposals, school and teacher Web sites, samples of student work during observed lessons, teachers’ lesson handouts and assessment rubrics, and statistic and survey data with regard to the schools from the California Department of Education and the California Technology Assistance Project. | N | N | A higher perecentage of the high-SES students had access to computers and internet at home, so those teachers reported spending less time teaching computer basics than did the teachers at low-SES schools. Low-SES schools also had higher percentages of English learners, several teachers pointed out the difficulties of teaching limited English speakers to use the Internet because they were regularly unable to key in URLs and search terms correctly or interpret the results of online searches. It was found that both high and low SES schools used the technology quantitavely about the same amount, but the high-SES students were able to diversify the use of the available technology as more advances classes were offered at their schools, so high-SES students demonstrated overall greater academic preparation. | Both hypotheses were confirmed, having greater access to computers at low-SES schools did help those students to increase their academic preparation. At the same time, having equal amounts of technology at high-SES schools did help those students to achieve even more. | It's not clear that technology access in schools increased the digital divide between high and low SES students, but this study did highlight the divides that already exist. | N | NA | Kind Of | The time required to conduct these interviews and the limited number of schools and teachers willing to dedicate the time to participate | Y | Con: As this study helps demonstrate, placing computers and Internet connections in low-SES schools, in and of itself, does little to address the serious educational challenges faced by these schools. To the extent that an emphasis on provision of equipment draws attention away from other important resources and interventions, such an emphasis can in fact be counterproductive. A more important concept for us, highlighted by this study, is that of the social embeddedness of technology. This concept suggests that technology does not exist outside of a social structure | 7 | 6 | Y |
| Ryan | RJ-004 | 10/16/18 | Mental Health | How screen-based sedentary behavior effects adolescent girls physical, behavioral, and psychosocial health indicators. | The Health Indicators Associated With Screen-Based Sedentary Behavior Among Adolescent Girls: A Systematic Review | Costigan, SA ; Barnett, L ; Plotnikoff, RC ; Lubans, DR | Journal of Adolescent Health, Volume: 52, Issue: 4, Pages: 382-392, 2013 | 10.1016/j.jadohealth.2012.07.018 | Q1 | 4.098 | 77 | Yes | I included this source because it provides a systematic review of how screen-based sedentary behavior effects different health indicators in adolescent girls that includes mental health aspects | The objective of this review was to investigate the association between recreational screen-based sedentary behavior and the physical, behavioral, and psychosocial health indicators for adolescent girls. | NA | Y | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| Samantha | SV-002 | 10/16/18 | Educational Equity | What factors facilitate teacher skill, teacher morale, and perceived student learning in technology-using classrooms | What factors facilitate teacher skill, teacher morale, and perceived student learning in technology-using classrooms? | Baylor, Amy L., Ritchie, Donn | Amy L. Baylor, Donn Ritchie (2002) What factors facilitate teacher skill, teacher morale, and perceived student learning in technology-using classrooms, Computers & Education 39 (2002) 395–414 | 10.1016/S0360-1315(02)00075-1 | Q1 | 4.538 | 159 | Yes | This article framed student success with technology in the classroom as it related to the qualifications of the teachers and planning, leadership, curriculum alignment, professional development, technology use, teacher openness to change, and teacher non-school computer use. | What factors facilitate teacher skill, teacher morale, and perceived student learning in technology-using classrooms? What actions can school personnel take that most effectively lead to their desired results regarding the integration of technology in schools? | NA | N | 1 | 0 | 1 | 1 | 94 classrooms from 12 total school in four states in different geographic regions of the country (5 from California, 2 from Florida, 3 from Virginia, 2 from Washington). Some elementary schools, some middle schools, some high schools. | CS | NA | 7 independent factors related to school technology (planning, leadership, curriculum alignment, professional development, technology use, teacher openness to change, and teacher non-school computer use) | Teachers from the 94 classrooms were interviewed and were asked a series of questions to best rank from 1=strongly disagree to 5=strongly agree each of the 7 categories, and cross referenced with a questionaire for the administrator of the school and the Technology Usage Plan (TUP) to create a chart with numerical scores | 5 | Y | NA | N | NA | NA | five dependent measures in the areas of teacher skill (technology competency and technology integration), teacher morale, and perceived student learning (impact on student content acquisition and higher order thinking skills acquisition). | Using the same interviews, questionaires, and TUPs that were mentioned in column Z, 5 additional rows to the chart were made and numerical scores were assigned in those categories as well. Stepwise regression resulted in models to explain each of the five dependent measures. | 5 | Y | N | NA | N | N | Teacher technology competency was predicted by teacher openness to change. Technology integration was predicted by teacher openness to change and the percentage of technology use with others. Teacher morale was predicted by professional development and constructivist use of technology. Technology impact on content acquisition was predicted by the strength of leadership, teacher openness to change, and negatively influenced by teacher non-school computer use. Technology impact on higher-order thinking skills was predicted by teacher openness to change, the constructivist use of technology, and negatively influenced by percentage of technology use where students work alone. | NA | NA | N | NA | Y | "While we could have had each teacher make a global assessment of student performance based on overall recollection of activities over the year, it would be significantly less precise than going through each activity and mathematically computing the assessment. Consequently, we limited the elaboration of
activities to three, which were randomly selected." They did not obtain teacher assessment of student proficiency given that there is nothing for the teacher to compare the class to (except to previous classes which may not have engaged in the same technology activities). | Y | Both: The predictors for the outcomes are well defined here and in cases where schools don't have the means to make sure the positive predictors are implemented, they might not be able to expect as high of a positive outcome, which supports the Con side. However, the Pro side could argue that administrative and teacher education programs are simple and relatively inexpensive to implement, so any school regardless of SES could expect to find successes in implementing 1:1 programs | 9 | 9 | Y |
| Blake | BP-008 | 10/16/18 | Attitude and Beliefs (Second order barrier) | Do teachers' personal technology beliefs/teaching beliefs affect integratio of technology? | The role of value on teachers' internalization of external barriers and externalization of personal beliefs for classroom technology integration | Vanessa W. Vongkulluksn, Kui Xie, Margaret A. Bowmana | COMPUTERS & EDUCATION
Volume: 118 Pages: 70-81
DOI: 10.1016/j.compedu.2017.11.009
Published:MAR 2018 | 10.1016/j.compedu.2017.11.009 | Q1 | 4.538 | 3 | Yes | This study is specifically investigating teachers' beliefs and the roles they play in integrating technology and receiving support on first-order barriers from the school/administrators. Includes a large sample size from the Midwest, perhaps making it more releveant to our case. | 1. How does actual school support affect teachers' perceived support on first-order barriers (internalization process)? How is this relationship influenced by teachers' value beliefs?
2.
How does teachers' perceived support on first-order barriers affect their classroom technology integration practice (externalization process)? How is this relationship influenced by teachers' value beliefs? | the relationship between perceived support on first-order barriers and classroom technology integration practice may also be mediated (pathway #3) and/or moderated (pathway #4) by the value beliefs variable. In addition, we hypothesized that perceived support on first-order barriers has a positive overall relationship with teachers' classroom practice with technology (externalization process).
| N | 2 | 0 | 2 | 2 | The sample for this study was 624 sixth-to twelfth-grade teachers and 20 administrators from 16 schools across a Midwestern state in the United States. There were 365 female and 259 male teachers. Of these, 157 teachers held a Bachelor's degree, 461 held a Master's degree, and 6 held a doctorate degree. The average teacher had about 13 years of teaching experience and about 24 students in his/her classroom. | CS | NA | perceived support on first-order barriers specified as the independent variable, value beliefs as the mediator, | 14 item survey, 5 point Lichert scales | 4 | Y | NA | N | NA | N | quantity and quality of classroom technology integration as the dependent variable, | Integration quantity was measured using a scale adapted from Wozney et al. (2006). Teachers were first asked to indicate whether or not they use the following technologies in their classroom: desktop computers, laptop computers, digital camera/camcorders, digital microphone, DVD player/recorder, internet, tablets, mobile phones, projectors, smart interactive whiteboards, audio/video conferencing system, student response systems (e.g., clickers), and Web 2.0 Technologies (e.g., Google Classrooms, Google Drive, Google Hangout, etc.). Teachers were also asked to list additional technologies they use that were not on the list. Subsequently, teachers were asked to indicate: “on average, what percentage of class time do you spend using these technologies?” Teachers' numeric percentage response was used as their integration quantity score.
Integration quality was measured using an 11-item Classroom Technology Practice scale created in a previous study (Kim, Cheng, & Xie, 2017). Four items asked respondents to indicate whether they typically use technology to engage in specific instructional activities, including student presentation, group collaboration, individual student work, and provision of feedback (Check all that apply; Yes = 1, No = 0). | 5 | Y | Y | Ability beliefs, teaching experience, value beliefs | Y | Y | value beliefs mediate and moderate the relationship between how perceived support on first-order barriers influences both the quantity and quality of classroom technology integration (i.e. the extent to which teachers used technology to enhance student-centered and critical-thinking tasks). These results suggest an interaction pattern called moderated mediation, an empirical relationship in which there is both a mediation effect as well as a moderated indirect effect where perceived support moderates how value beliefs predict classroom practice with technology (Muller et al., 2005, Preacher et al., 2007). Further, our results show that these salient effects of value beliefs on classroom technology integration practice still hold after taking into account other teacher-level differences such as teaching experience and ability beliefs for technology use. Similarly, previous qualitative studies have shown value beliefs to be one of the most proximal determinants of teachers' classroom practice with technology (Miranda and Russell, 2012, Wozney et al., 2006). Beyond a barrier threshold of technology access, the way in which teachers translate perceived school support into classroom practice is filtered through their belief system regarding the usefulness and practicality of technology to lead to improved instruction and student outcomes (Ertmer et al., 2012). The present study provides further empirical evidence supporting these findings. Specifically, the results suggest that value beliefs moderate the extent to which teachers translate actual school support into perceived support on first-order barriers. Teachers who believe that technology is valuable in the classroom tend to amplify the access they have and place less weight on access constraints when they make judgments about how much external barriers exist in their school context. | both | NA | Y | Tried to eliminate bias associated with self-reported data by verifying it through multiple survey types and by "checking" the teachers' responses with administrators and technology specialists for accuracy/honesty. Also ran multiple models to make sure the correlations acutally existed, often attempting to single out more specific variables and creating multiple models to come to conclusions. | Y | This study has limitations that stem from certain logistic and contextual constraints. The first limitation is a result of the use of self-report surveys, particularly for our technology integration indices. We were not offered the opportunity to observe classrooms or interview teachers, which would have provided more objective measures of classroom technology integration. As such, our results may be skewed due to the self-report bias that is present when subjects are asked to report their own behaviors (Greene, 2015). Although we noted that self-report surveys are typically used in studies referencing the Barriers to Technology model (e.g. Hixon and Buckenmeyer, 2009, Kopcha, 2012, Miranda and Russell, 2012, Mueller et al., 2008), we endeavored to minimize this bias through collecting multiple types of survey data. This includes asking teachers to assess the percentage of classroom time for which they integrate technology, complete a checklist of the types of instructional practice for which they use technology, and use Likert-scale measures to indicate perceptions that could not be tapped otherwise. In order to avoid the sole use of teachers' self-reported perceptions, we also sourced data from school administrators and technology specialists. They provided us with more objective measures of technology access, including the number of devices available in each school. Relatedly, another limitation of the study is a consequence of using quantitative measures to explain the complex phenomenon of technology integration. Again, teachers' qualitative narratives would have bolstered our understanding of technology integration in each specific classroom. However, our aim is to empirically corroborate the qualitative accounts of the role of value beliefs as documented in previous studies, and the use of quantitative methods is appropriate for this purpose. Our study also followed a clear theoretical model, which delineated relationships among different belief and behavior variables. As such, we could reasonably use the deductive, quantitative approach to answer our research questions instead of more inductive, qualitative methods.
| Y | Neither: though perhaps a bit more on the con side considering that improper implementation due to value beliefs can defeat the purpose of having technology in the classroom. Just helps to show that second-order barriers do in fact exist and have an impact on implementation of technology in classrooms. | 9 | 8 | Y |
| Samantha | SV-003 | 10/16/18 | Educational Equity | How is the success of technology in schools different across ethnic and gender gaps? | New technologies, new differences. Gender and ethnic differences in pupils' use of ICT in primary and secondary education | Volman, M (Volman, M); van Eck, E (van Eck, E); Heemskerk, I (Heemskerk, I); Kuiper, E (Kuiper, E) | Van Eck, E, Heemskerk, I, Kuiper, E, Volman, Monique, Van Eck, Edith, Heemskerk, Irma, & Kuiper, Els. (2005). New technologies, new differences. Gender and ethnic differences in pupils' use of ICT in primary and secondary education. Computers & Education, 45(1), 35-55. | 10.1016/j.compedu.2004.03.001 | Q1 | 4.538 | 112 | Yes | This article looks less at low vs high SES and more at the ethnic and gender implications of technology in schools. This is an angle that has not yet been covered by any of the other potential studies. | • to what extent do gender differences and ethnic differences exist in participation in using ICT
applications?
• to what extent do gender differences and ethnic differences exist in ICT skills and learning outcomes
of pupils using ICT applications?
• to what extent do gender differences and ethnic differences exist in the attitude of pupils towards
ICT applications?
• to what extent do gender differences and ethnic differences exist in the approach of pupils in
their use of ICT applications? | NA / Past research shows that girls are less enthusiastic about ICT and ethnic minorities are typically at a lower SES and so might correlate with expectations for lower inate computer skills | N | 1 | 0 | 1 | 1 | 7 schools in the Netherlands, some primary schools and some secondary schools. 213 students filled out questionaires, interviews conducted with 48 students and 12 teachers. The ethnic minority pupils in our sample were mainly coming from Moroccan, Turkish and
Surinamese lower-SES families, with at least one parent not being born in the Netherlands. | CS | NA | Gender, ethnic minority vs majority | Students self identified as members of the ethnic minority or majority, and as male or female | 5 | Y | NA | N | NA | N | participation, ICT skills, learning outcomes, attitude and approach | The outcome variables from each category were broken down into striaghtforward yes or no questions, which were administered to the students as a questionnaire, responses were measured as percentages of yes or no responses. | 4 | Y | N | NA | N | N | It was found that gender differences are nominal, but there does exist a difference in the attitudes of ethnic minority and majority students at all ages. | The hypothesis that students from ethnic-minority backgrounds have different attitudes and perceived skill levels was demonstrated to hold true here | The hypothesis that girls had different interests in ICT than boys was not supported here at the primary school level, but at the secondary school level it was clear that girls and boys preferred to use technology very differently. | N | NA | N | A limitation of our study is that we focussed on averages: mean group scores of girls and boys, and of pupils from an ethnic minority background versus from the majority population. Individuals, however, will not always fit this group average. Moreover, the category ‘ethnic minority pupil’ is a very broad category. It should be noted that in our sample it consists mainly of pupils from Moroccan, Turkish and Surinamese lower-SES families. Our response group, especially in secondary education, was too small to further distinguish between ethnic groups in a valid way, or to explore the possible interaction between gender and ethnic group. | Y | Neither: I'm not sure that any of this data helps any one side at all, it just highlights some of the differences in perceptions and preferred uses of technology by the populations analyzed. These results don't necessarily hurt the case that techology should be implemented in schools, nor does it really advocate for it. The information presented here presents more of an interesting side note that different people may approach the use of technology in schools from different angles. These differences don't necessarily need to be accomodated, but they should be acknowledged by both sides. | 5 | 4 | Y |
| Blake | BP-009 | 10/16/18 | Second-order barriers | Do teachers' personal technology beliefs/teaching beliefs affect integratio of technology? | Teachers’ Conceptions of Technology, School Policy and Teachers’ Roles When Using Technology in Instruction | Samuel Obara, Bikai Nie, John Simmons | Obara, S., Nie, B., Simmons, J. (2018). Teachers’ Conceptions of Technology, School Policy and Teachers’ Roles When Using Technology in Instruction. Eurasia Journal of Mathematics, Science and Technology Education, 14(4), 1337-1349. https://doi.org/10.29333/ejmste/83569 | 10.29333/ejmste/83569 | Q3 | 0.903 | 0 | Yes | Case study following teachers in a specific subject area and how their individual conceptions of technology and the policy/support relating to technology in their school affected the use and implementation of technology in the classroom. | What are the roles that teachers played in the implementation process of technology in the classroom according to their conceptions of technology and school policy on technology? | NA | N | 1 | 0 | 1 | 1 | 3 | CS | NA | conceptions of technology and school policy on technology | Interview data | 3 | IDK | Initial interview data was used to then adjust protocol for follow-up interviews | N | NA | N | use of technology in mathematics classes | Teacher evaluations/observations by researchers | 3 | IDK | N | NA | N | Y | Teachers’ conceptions of technology and school policy on technology, had an impact on technology implementation. The impact on technology implementation was largely affected by how the policy encouraged or discouraged the teachers in their efforts to use computing technology (computers and calculators) in their mathematics teaching. Also that participants’ conceptions and understanding of computing technology’s educational roles evolved from simple tools for productivity and motivation to diverse and advanced roles for learning concepts and developing thinking skills | NA | NA | N | NA | N | This study was designed to gain insight into teachers’ and administrators’ conceptions of policy and its impact on technology implementation. It was a quest to determine what the policy is and to what extent the participants had embraced it. The analysis presented in this study did not offer a policy implementation model or make generalizations about the policy process or the technology implementation process in education. Neither did it explore the participants’ prior experiences that may have contributed to their conceptions. The study did not investigate the process of choosing hardware or software titles, the appropriateness of software titles, the teachers’ level of technology use ability or the teachers’ technology pedagogical knowledge for teaching mathematics. Rather, it presented an account of the understanding of technology policy “always under construction” and applied sense-making perspectives to the study of technology policy as a process. | Y | Neither: though the study was meant to provide information on how teachers' conceptions of technology affects their use of it, due to the sample size and methodology of this study, this would not be useful to either side. | 5 | 4 | N |
| Sam | SM-003 | 10-16-18 | Implementation | The implementation of a 1:1 technology program's effect on teachers technological self-efficacy | Technology-Literate School Leaders in a 1:1 iPad Program and Teachers' Technology Self-Efficacy
| John M. Hineman, Tiffany T. Boury, George W. Semich
| Source Title: International Journal of Information and Communication Technology Education (IJICTE) 11(2)
Copyright: © 2015 |Pages: 12 | 10.4018/ijicte.2015040106
| Not on the page | not on page | 0 | Yes | A detailed study on the influence of efforts undertaken by technology-literate school leaders to facilitate the implementation of a school-wide 1: 1 iPad program and the subsequent influence those efforts had on teachers' technology self-efficacy. | 1. What efforts were involved in implementing the 1:1 iPad program?
2. How has teachers’ technology self-efficacy been influenced as a result of the efforts undertaken to implement the 1:1 technology program? | NA | N | 1 | 0 | 1 | 1 | not viewable in the available part of the article | CS | NA | Data provided by focus group | not stated | NA | NA | NA | N | NA | N | Teacher self-efficacy | Not stated | NA | NA | No | NA | N | N | None | NA | NA | No | NA | Yes | none that can be viewed | Y | Neither... I can't get the full study | 5- it could be with full access | NA | N |
| Sam | SM-004 X | 10-16-18 | Learning and impacts on teaching
| What are the impacts of 1:1 tech on learning and teaching
| Technology Promoting Student Excellence:
An investigation of the first year of 1:1 computing in New Hampshire middle schools | Damian Bebell | Bebell, D. (2005). Technology promoting student excellence: An investigation of the first year of 1: 1 computing in New Hampshire middle schools. Boston, MA: Technology and Assessment Study Collaborative, Boston College. Retrieved August, 26, 2008. | | not on the web of science | NA | NA | Yes | The current paper presents a program evaluation of the initial nine months of a 1:1 laptop program across six New Hampshire middle schools. The analysis of the New Hampshire data reflects many of the most cited benefits of 1:1 computing including: increased teacher and student use of technology across the curriculum, increased student engagement and motivation, and improved teacher-student interactions. | How does the implementation of a 1:1 tech program effect the teachers and students of New Hamp. Middle schools | NA | N | 1 | 0 | 1 | 1 | ... | CS | NA | 1:1 technology program instatement | many different ways sometimes (time (min) and catagorical variables) | 5 | Y | None | N | NA | No | Again, many different things (success in different fields) | various ways | 4 | Y | NA | NA | N | N | NA | NA | NA | No | NA | Yes | limitations of time and budget are the main ones stated | Y | Pro- every catagory seems to be improved by tech | 8 | 8 | Y |
| Samantha | SV-004 | 10/16/18 | Educational Equity | What contributes to creating the digital divide? | Factors influencing digital technology use in early childhood education | Courtney K.BlackwellAlexis R.LauricellaEllenWartella | Courtney K.Blackwell, Alexis R.Lauricella, EllenWartella, "Factors influencing digital technology use in early childhood education". Computers & Education, Volume: 77 Pages: 82-90, August 2014 | 10.1016/j.compedu.2014.04.013 | Q1 | 4.583 | 45 | Yes | Overall, the study provides the first path model investigating early childhood educators’ technology use and provides practical considerations to aid teachers’ use of technology in the classroom. The study has enough breadth to also account for SES of teachers, and focuses on what causes the digitial divide. | What causes the digitial divide in early educational technology use and what factors influence the divide? | H1. Teachers with higher perceived support from their schools have higher levels of confidence, more positive attitudes, and higher technology use compared to teachers with lower perceived support. H2. Having a school technology policy positively influences teacher attitudes, confidence, and technology use. H3. Teachers whose students are from lower socioeconomic backgrounds have more positive attitudes toward using technology in the classroom and use technology more frequently compared to teachers whose students are from higher socioeconomic backgrounds. H4. Teachers with more teaching experience have less favorable attitudes toward technology and use technology less often than teachers with less experience. 2.2. Second-order barrier hypotheses H1. Teacher confidence using technology in developmentally appropriate ways has a positive influence on technology use and mediates the relationship between support and technology policy on technology use. H2. Teacher attitudes toward the value of technology for children’s learning have a positive influence on technology use and mediate the relationship between support, technology policy, student SES, and teaching experience on technology use. | N | 1 | 0 | 1 | 1 | 1234 U.S. early childhood educators working with children 0–4 years of age pulled from a larger data set from an online survey, all affiliated with NAEYC | CS | NA | access to and use of multiple technologies, as well as their attitudes toward technology and their perceived level of support | Online survey data about types of technology used, frequency of use, comfort level, etc. converted to a numeric scale. | 4 | Y | NA | N | NA | NA | Correlations between attitudes, technology use, student SES, confidence, technology policy | Correlation models were used to relate each factor to the other factors and obtain a path analysis for prediction. | 3 | Y | N | NA | Y | Y | attitudes toward the value of technology to aid children’s learning have the strongest effect on technology use, followed by confidence and support in using technology. Additionally, student SES has the strongest effect on attitudes, while support and technology policy influence teacher confidence, which in turn influences attitudes. In contrast, more experienced teachers have more negative attitudes | the first-order barriers of support, technology policy, student SES, and teaching experience would both directly influence technology use and have indirect effects on use through the second-order barriers of confidence and attitudes | NA | N | NA | Kind of | while the model has a good overall fit, only 11% of the variance in technology use, 9% in attitudes, and 3% in confidence was explained by the model. Thus, there are other omitted variables that help predict more of the variance in technology use, attitudes, and confidence. One key factor not captured by this model is teachers’ general pedagogical beliefs, as teachers who have more traditional teaching beliefs tend to have more negative attitudes toward technology while teachers with more student-centered orientations tend to have more positive attitudes. Participants were only NAEYC members. They also generalized technology usage without looking at how different devices have different impacts on students. | N | Con: teacher attitudes and technology policy are the strongest predictors of successful technology implementation, and student SES is a strong indicator of teacher attitudes on technology. If low SES students are given 1:1 technology in the same way as higher SES students, according to this information they will be unlikely to be as successful. The scope of the article is also small and it never really took into account the SES of teachers. | 5 | 7 | Y |
| Lydia | LF-005 X | 10/17/18 | Health | How does screen time affect vision in students? | Low-energy light bulbs, computers, tablets and the blue light hazard | O'Hagan, J B ; Khazova, M ; Price, L L A | Ohagan, J. B., Khazova, M., & Price, L. L. (2016). Low-energy light bulbs, computers, tablets and the blue light hazard. Eye, 30(2), 230-233. doi:10.1038/eye.2015.261 | doi:10.1038/eye.2015.261 | Q2 | 2.478 | 12 | Yes | This study analyzing the damaging effects of blue light from LED lights and screens on eyes compared to "natural" light. This would be an important factor to consider when implementing 1:1 tech. | To provide a comparison with natural exposures to blue light | NA | N | 1 | 1 | 0 | Study 1 | 26 | CS | NA | NA, this was a descriptive study collecting data on blue light exposure from different sources and comparing them. | NA | NA | NA | NA | N | NA | N | The spectral irradiance incident on the earth in southern UK; A range of lamps (CFL and LED), computer screens, tablet computers, laptops, and smartphones were assessed for comparison with the blue light hazard exposure limit. | Measurements were made using an Exemplar Plus CCD array spectroradiometer, S/N 655, coupled by a metal jacketed QP600-2-SR/BX optical fibre to a D7-H diffuser, S/N 10083. The system was calibrated using 1000Wtungsten–halogen lamps, calibrated for spectral irradiance to the Physikalisch Technische Bundesanstalt traceable reference standards, S/N 548. | 5 | Y | N | NA | N | N | In conclusion, under even extreme long-term viewing conditions, none of the assessed sources suggested cause for concern for public health. The worst assessed source consisted of three indicator LEDs, which were unlikely to be viewed close up for long enough to cause concern. However, these sources were representative of indicator lamps that did not require the assessed luminance for their intended function. The percentage transmission of blue light from the corneal surface to the retina is age related, with the transmission for children higher than for adults. Therefore, where such sources are uncomfortable to view for adults, they could be distressing for children | NA | NA | N | This is a descriptive study that is not trying to find explanations, but measure the blue light emissions of different sources. | Y | The impact of the blue light from the studied sources on circadian rhythm and sleep quality was outside of the scope of this study. This study does not address the implications of exposure to light for effects other than retinal damage | Y | Both: The results suggest that blue light emissions from technology are not a major public health concern for damage to the retina. However, blue light is much more distressing to children than to adults as this is an age related effect. | 7 | 7 | Y |
| Lydia | LF-006 | 10/19/18 | Health | Metabolic risk from screen time in children | Screen Time and Metabolic Risk Factors Among Adolescents | Hardy, LL; Denney-Wilson, E; Thrift, AP; Okely, AD; Baur, LA | Mark, A. E., & Janssen, I. (2008). Relationship between screen time and metabolic syndrome in adolescents. Journal of Public Health, 30(2), 153-160. doi:10.1093/pubmed/fdn022 | doi:10.1093/pubmed/fdn022 | Q2 | 1.67 | 132 | Yes | This study looks at the relationship between screen time among adolescence and metabolic syndrome. Implementing 1:1 tech would mean being versed in the potential health implications and how to mitigate the risks. | The primary objective was to determine the dose–response relation between screen time (television þ computer) and the metabolic syndrome (MetS) in adolescents. | NA | N | 1 | 0 | 1 | Study 1 | 1803 | CS | NA | Screen time | Screen time included television, video and computer game use, and was ascertained as part of the physical activity questionnaire, which was completed in the home interview or MEC depending on the survey round and age of the participant. | 4 | Y | NA | N | NA | N | The presence of metabolic syndrome | MetS was defined as having 3 of the following: high triglycerides, high fasting glucose, high waist circumference, high blood pressure and low HDL cholesterol. Subjects were seated and rested quietly for 5 min before three blood pressure measures were obtained on the right arm using a mercury sphygmomanometer. Waist circumference was measured to the nearest 0.1 cm at the level of the iliac crest at the end of a normal exhalation. Blood samples for HDL cholesterol and triglycerides were analysed at the Johns Hopkins University Lipoprotein Analytical Laboratory. | 5 | Y | Y | Socio-demographic info, physical activity, and dietary measures. | N | N | The primary finding was that the likelihood of having the MetS increased in a gradient dose–response manner as daily screen time hours increased, irrespective of physical activity level. Adolescents reporting screen times of 3 h/day were approximately two- to threefold more likely to have MetS than were adolescents with daily screen time levels of 1 h or less. | NA | NA | Y | They controlled for other variables with data collected during the experiment, such as age and level of physical activity. | Kind Of | The primary study limitation was the cross sectional and observational nature, which prevents us from making causal inferences about the relation between screen time and MetS. The other main limitation was the self-reported measures of screen time and physical activity. | Y | Con: Screen time was independently correlated with metabolic syndrome and had a dose-dependent effect, implying that additional screen time would increase risk of metabolic syndrome. | 8 | 8 | Y |
| Colin | CB-007 | 10/21/18 | Educational Impact (Lecture Comprehension/Distraction) | Do students multitasking on a laptop comprehend as much of a lecture as non-multitasking peers? Do multitasking peers affect the comprehension of those around them? | Laptop Multitasking Hinders Classroom Learning for Both Users and Nearby Peers | Sana, F., Weston, T., Cepeda, N. J. | Sana, F., Weston, T., and Cepeda, N. J. Laptop Multitasking Hinders Classroom Learning for Both Users and Nearby Peers | doi:10.1016/j.compedu.2012.10.003 | Q1 | 4.538 | 119 | Yes | It's an experimental study that demonstrates that multitasking affects the comprehension of everyone in a lecture. | Does multitasking hinder comprehension, and does this effect spread to peers who are in sight of multitaskers. | Expt 1: We hypothesized that participants who multitasked while attending to the lecture would have lower comprehension scores compared to participants who did not multitask.
Expt 2: We hypothesized that participants who were seated in view of multitasking peers would have lower comprehension scores compared to participants who had minimal or no visual distraction from multitasking peers. | N | 2 | 2 | 0 | Study 1 and Study 2 | 40, 38 | CS | NA | Study 1: Multitasking
Study 2: Distance to multitasker | For study 1, participants who were in the multitasking group were assigned small tasks that would require them to spend ~1/3 of the lecture period using their laptops for extraneous purposes.
For study 2, strategic placing of alternate set of participants was employed to make sure participants were in view of someone multitasking | 5 | Y | NA | Y | Study 1: One set of students was told to take computer notes without multitasking. An experimenter monitored usage from the back of the classroom.
Study 2: One set of students was strategically placed so that they were not in view of multitaskers. | Y | Performance on a post-lecture comprehension test | A post-lecture test consisting of both simple recall questions and | 4 | Y | Y | Pre-lecture knowledge on the subject, age, gender, English fluency, high school GPA | Y | Y | Study 1: "Overall, participants who multitasked scored 11% lower on a post-lecture comprehension test."
Study 2: "These findings suggest that peer multitasking distracted participants who were attempting to pay sole attention to the lecture. Those in view of a multitasking peer scored 17% lower on a post-lecture comprehension test." | 1 & 2 | NA | Y | They removed participants with too much prior knowledge on the lecture subject, and demonstrated homogeneity across the other variables in column AL. Also checked for consistency in note quality between groups. | Kind Of | Did not directly measure attention | Y | Con: Inappropriate use of computer resources during class demonstrably decreases the performance of not only students who multitask, but also those around them. | 6 | 7 | Y |
| Blake | BP-010 | 10/22/18 | Second-order barriers | Do second order barriers affect the implementation and success of technology integration? | Factors related to pedagogical beliefs of teachers and technology integration | Shih-Hsiung Liu | COMPUTERS & EDUCATION
Volume: 56 Issue: 4 Pages: 1012-1022 May 2011 | 10.1016/j.compedu.2010.12.001 | Q1 | 4.538 | 47 | Yes | This study surveyed over 1,000 elementary school teachers to examine the relationship and potential conflict between teacher beliefs (second order barrier) and technology integration. This study also looked at whether or not those beliefs were teacher-centered or student-centered and provided a great deal of statistical analysis of the results. | 1.
Do most teachers hold learner-centered beliefs or teacher-centered beliefs about technology use during instruction? Are teacher beliefs and teaching activities consistent?
2.
What are the differences between teacher beliefs and teaching activities in each factor associated with technology use? | NA | N | 1 | 0 | 1 | Study 1 | 1120 | CS | NA | Teacher beliefs | The pedagogical beliefs section had nine item pairs. For example, an item for
learner-centered pedagogical belief was “Most learning should be from classroom discussion. Permitting interaction among learners
motivates learners and promotes the development of learning abilities.” Conversely, an item for teacher-centered pedagogical belief was “For
effective learning, students must pay close attention to lectures. A classroom must be silent except for the teacher’s voice.” Responses to each
item were on a two-point scale, with 1 representing a “teacher-centered pedagogical belief” and 2 representing a “learner-centered
pedagogical belief.” The Kuder-Richardson reliability of the section was 0.74. If the total score for 9 items exceeded 13.5, the respondent held
learner-centered pedagogical belief; conversely, if the total score was less than 13.5, the respondent held teacher-centered pedagogical belief. | 4 | Y | A bunch of statistical stuff (section 4.1 of article) | N | NA | N | Technology use/integration | item-pair scenarios | 2 | IDK | Y | Factors associated with technology integration derived from open-ended questionnaires and then compiled into 30 "categories" | Y | Y | Student achievement was the principal factor influencing teacher decisions about using technology, especially for teachers who held learner-centered beliefs. | NA | NA | Y | Performed other statistical analysis and referenced other studies/sources to address some of the inconsisitencies they experienced in their analysis. Also took into consideration and addressed the unique atmosphere of Taiwan and its educaiton system. | Kind Of | No real limitations were listed other than the fact that they recognized the many other factors that affect why a teacher may implement technology and the fact that their study focused specifically on Taiwan, when in reality, they said a cross-nation study should be done to reach a more "gerneralizable" conclusion. | Y | Neither: since this study basically admitted to finding nothing particularly new or anything that could be solidified by previous studies, neither side could really use this other than for background knowledge or perhaps to be aware of some different barriers/influences teachers experience when looking to implement technology. | 4 | 5 | N |
| Blake | BP-011 | 10/22/18 | second-order barriers | do second order barriers affect the implementation and success of technology integration? | iPads in the classroom: what do teachers think? | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| Blake | BP-012 | 10/22/18 | pedagogical beliefs | do second order barriers affect the implementation and success of technology integration? | Understanding the relationship between teachers’ pedagogical beliefs and technology use in education: a systematic review of qualitative evidence | Tondeur, J; van Braak, J; Ertmer, P; Ottenbreit-Leftwich, A | ETR&D-EDUCATIONAL TECHNOLOGY RESEARCH AND DEVELOPMENT
Volume: 65 Issue: 3 Pages: 555-575
DOI: 10.1007/s11423-016-9481-2
Published:JUN 2017 | 10.1007/s11423-016-9481-2 | Q2 | 1.728 | 14 | Yes | This systematic review of 14 related articles discusses important relationships regarding second-order barriers and how they affects teachers' implementation and understanding of technology in the classroom. Very good to look over and build personal knowledge base. | Investigate links between teachers’ pedagogical beliefs and their educational uses of technology through review of 14 other studies. 5 core areas- (1) the bi-directional relationship between pedagogical beliefs and technology use, (2) teachers’ beliefs as perceived barriers, (3) the association between specific beliefs with types of technology use, (4) the role of beliefs in professional development, and (5) the importance of the school context | NA | Y | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| Ryan | RJ-005 | 10/22/18 | Mental Health | Independant association of screen time on mental health | The Independent and Interactive Associations of Screen Time and Physical Activity on Mental Health, School Connectedness and Academic Achievement among a Population-Based Sample of Youth | Linda Trinh PhD1; Bonny Wong MA1; Guy E. Faulkner PhD1 | Journal of the Canadian Academy of Child and Adolescent Psychiatry, Volume: 24, Issue: 1, Pages 17-24, 2015 | NA | Q1 | 1.8 | 10 | Yes | This study shows independent associations of screen time on not only mental healh but also school connectedness | The purpose of this study is to examine the independent effects of PA and screen time on mental health, school connectedness and academic achievement, and potential interactions between PA and screen time in such associations. | that higher screen time among youth would be associated with poorer mental health and academic outcomes. The combined effects of physical activity and screen time on mental health outcomes remain exploratory | N | 1 | 0 | 1 | Study 1 | 9241 | CS | NA | Screen Time and Physicaly Activity | Students were given a questionnare asking how much time they spent both physically active and how many hours a day on average they spend in front of a screen. | 4 | Y | NA | N | NA | N | Psychological Distress, Depression, Self-esteem, School disconnectedness, and perceived academic achievement | Various questionnaires that have been demonstrated to be valid and reliable were used to measure these effects | 4 | Y | N | NA | Y | Y | In this study, higher screen time was consistently associated with poorer mental health, school disconnectedness and academic achievement independent of PA levels | 1 | NA | N | NA | Y | Observed the limitations of the use of self-reporting measures that could lead to measurement error and response bias. | Y | Con: High screen time was independantly associated with poorer mental health and academic outcomes in Ontario youth and the effects of high screen time are greater than the independent associations of physical activity among these outcomes. | 7 | 6 | Y |
| Daniel | DM-004 | 10/22/18 | Implementation: Professional Development | How well does professional development work? | What Makes Professional
Development Effective? Strategies
That Foster Curriculum Implementation | Penuel, WR; Fishman, BJ; Yamaguchi, R; Gallagher, LP; | Journal : American Educational Research Journal; Volume 44; Issue 4; Pages 921-958 | 10.3102/0002831207308221 | Q1 | 2.462 | 347 | Yes | Even though it does not focus on technology specifically, it does analyze the efficacy of professional development in general, which is related to the topic at hand. | (a) What kinds of professional development activities in
GLOBE are associated with increased levels of program implementation?
(b) What kinds of professional development activities in GLOBE are associated
with increased teacher knowledge and changes to science teaching practice?
(c) How do support and follow-up after professional development
influence program implementation and teacher knowledge and changes to
science teaching practice? | NA | N | 2 | 0 | 2 | Study 1 | 454 teachers | CS | NA | data reporting, protocol use,
and preparation for student inquiry | Protocol use is a binary variable (1 = yes, 0 = no) showing whether teachers
implemented the GLOBE protocols in their class. Data reporting is a binary variable that measures whether teachers
reported data on the GLOBE Web site Protocol use is a binary variable (1
yes, 0
no) showing whether teach
ers
implemented the GLOBE protocols in their class.. | 5 | Y | NA | N | NA | N | (a) barriers, (b) equipment, (c) technology support,
(d) reform-like professional development, (e) traditional professional
development, (f) time span, (g) coherence, and (h) collective participation.
Teacher characteristic variables are (a) graduate degree; (b) elementary, middle,
or high school teacher; and (c) science-education certification | Each variable had a different number scale as described in the paper underneath the dependant variable section (which is highlighted) | 5 | Y | N | NA | Y | Y | Our results indicate that the design elements of professional development
that mattered most for program implementation in GLOBE varied,
depending on the aspect of implementation being measured. To increase data
reporting, the most effective professional development strategy was to focuson promoting student inquiry in initial professional development sessions. In
other words, a unit increase in Focus on Student Inquiry increased the odds
of data reporting by 23%. For both protocol use and preparedness for student
inquiry, the opportunity to “localize” GLOBE—that is, to plan for how to tailor
its implementation to local circumstances of teachers’ classrooms—was a
significant predictor of the extent to which teachers implemented these
aspects of the program. In addition, a focus on the content of GLOBE was a
significant predictor of teachers’ feeling more prepared to implement student
inquiry in GLOBE. We found conflicting results for the effect of duration of
professional development and for the nature of the GLOBE partner providing
the professional development: More hours of professional development
supported greater protocol use but seemed to undercut a focus on student
inquiry, and university-based partners tended to do a better job supporting
protocol use, whereas reliance on school-based partners was associated with
less frequent use of student inquiry. | NA | NA | Y | Some aspects of the program design itself are likely to contribute to this
pattern of findings. For example, to engage in student inquiry, an initial hur
dle
that teachers must overcome is the tendency to collect but not report data
because of time constraints. Reporting data, however, makes it possible for
students and teachers to discuss and analyze data because the GLOBE Web
site can quickly produce charts and graphs of schools’ data | Y | Because we did not use a random-assignment design or seek to control
any partners’ approach to professional development, our study cannot speak
directly to the impact of professional development on teacher practice or on
student learning.Our study’s data have a further limitation, in that the pattern of responses
we received precludes us from saying that ours is a representative sample of
GLOBE teachers’ experiences. | N | Neither; this study demonstrates that the results wanted from professional development have to pe specifically targeted for. | 4 | 9 | N |
| Daniel | DM-005 | 10/22/18 | Implementation: Professional Development | Where should professional development focus in order to best help teachers and students? | Teacher value beliefs associated with using technology: Addressing professional
and student needs | Ottenbreit-Leftwich, AT; Glazewski. KD; Newby, TJ; Ertmer PA; | Journal : Computers and Education; Volume 55; Issue 3; Pages 1321-1335 | 10.1016/j.compedu.2010.06.002 | Q1 | 4.538 | 135 | Yes | This study looks at specifically what professional development should target to best help students and teachers. | This study sought to examine how and why teachers used technology to enhance teaching and learning in order to
understand teachers’ value beliefs related to technology use. More specifically, the study examined the teaching and learning goals teachers
addressed through classroom technology use. | NA | N | 1 | 0 | 1 | Study 1 | 8 teachers | CS | NA | Shared value beliefs between eight teachers who had exemplary technological implementation | To investigate value beliefs, an interview,
portfolio, and observation were collected from each teacher. | 3 | Y | NA | N | NA | N | The different ways that teachers tend to use technology in the classroom | The same interview, portfolio and observation that were used to find the independant variables. | 3 | Y | N | NA | Y | Y | Therefore, professional development should be designed to explicitly target teachers’ value beliefs, focusing on the values addressed
in this study. These value beliefs could be targeted by incorporating a “translation activity” into professional development
programs.
Translation activities should highlight how students might benefit from specific uses of technology. For example, a common topic for
professional development is presenting new grading software. | NA | NA | N | NA | Kind of | First, two data sources focused on teacher’s self-reports and perceptions.
Therefore, when discussing professional needs and student needs, these definitions were inferred based on the perceptions of these eight
award-winning teachers. Future research studies should incorporate more data sources to accurately measure value beliefs, or perhaps
develop a measurement tool to better assess teacher value beliefs.
Other limitations include those commonly associated with case studies. Although the sample was small, a large sample was not feasible.
Given that the samplewas limited to MCOATT recipients, the resulting implications may only apply specifically to this population | Y | Pro: This study shows that teachers can make highly effectave use of technology in the classroom, even if it is not specifically student oriented. | 6 | 7 | Y |
| Daniel | DM-006 | 10/22/18 | Implementation: Professional Development | How much professional development do teachers need? | A framework for teachers’ integration of ICT into their classroom practice | A framework for teachers’ integration of ICT into their classroom practice
| Donnelly, D; McGarr, O; O'Reilly, J | 10.1016/j.compedu.2011.02.014 | Q1 | 4.538 | 59 | Yes | The study builds a framework that the author believes can help speed the integration of technology into schools. | This research project is focused on the beliefs and practice of science teachers on the
integration of an ICT-based resource (the Virtual Chemistry Laboratory) to support scientific inquiry and how various knowledge areas are
highlighted through teachers’ use of the ICT-based resource. | NA | N | 1 | 0 | 1 | Study 1 | seven Science teachers and six educational stakeholders | CS | NA | The teacher's views on technology; the teacher's views on teaching | Teachers were interviewed before using a piece of technology and asked about their experiences with and views on technology in teaching. | 3 | Y | NA | N | NA | N | The success of the implementation of the technology | Teachers were observed teaching a class with the chemistry application, then were interviewed after the class had finished. The intervew asked for their feelings about the application, how they thought students handled it, and if they would use it again. | 3 | Y | N | NA | Y | Y | A framework was set up in order to explain the different attitudes and abilities observed among the teachers that were interviewd. The authors also included explanations oh how they believed, based on other research, teachers could move through the framework, and so implement technology better. | NA | NA | N | NA | Kind of | None were listed. | Y | Con: This study demonstrates the hit and miss nature of technological implementation and how it is dependant on teacher attitudes. | 7 | 5 | Y |
| Sam | SM-005 | 10/22/18 | Tech skills and wages | How do computer skills effect earnings, employment, and college enrollment? |
The effects of computers and acquired skills on earnings, employment and
college enrollment: Evidence from a field experiment and California UI
earnings records☆ | By:Fairlie, RW (Fairlie, Robert W.)[ 1,2 ] ; Bahr, PR (Bahr, Peter Riley)[ 3 ] | ECONOMICS OF EDUCATION REVIEW
Volume: 63 Pages: 51-63
Published:APR 2018
Document Type:Article | DOI: 10.1016/j.econedurev.2018.01.004 | Q2 | 1.293 | 0 | Yes | This actually gives info on students (albeit college students) given computers, (like a 1:1 tech program) and their grades and wages over a 7 year span. This source is also quite recent. | To test the association between having a computer for college and earnings in a job | NA | N | 2 | 1 | 1 | Experimental study (I guess one) | 141 | Longitudinal | 7 years | The presence of a home computer | Yes/no | 5 | IDK | One group was given computers and one was not | Y | A group of similar demographics that did not recieve a home computer | Yes | Wages after college | dollars | 5 | Y | Y | How many people actually found jobs and how the computer skills helped with that. | Y | N | The results of the study were that it was statistically insignificant so no claims of causation were made. | NA | NA | Y | They examined another study done that yeilded different results | Kind of | Although the results consistently show null effects, one limitation is that the estimates are not precisely estimated. | Y | Con: the presence of a home computer was not shown to give an edge to these students. | 7 | 8 | Y |
| Samantha | SV-005 | 10/23/18 | Educational Equity | What is the student experience like with online courses? | Distance education via the Internet: the student experience | Linda Carswell, Pete Thomas, Marian Petre, Blaine Price, and Mike Richards | Linda Carswell;Pete Thomas;Marian Petre;Blaine Price;Mike Richards, Distance education via the Internet: the student experience, British journal of educational technology. , 2000, Vol.31(1), p.29-46 | DOI: 10.1111/1467-8535.00133 | Q1 | 2.729 | ? | Yes | This study looks at how taking online courses (distance education) affects learning outcomes for college students. This may not be easily extrapolated but I think it's interesting to see how students are affected by online material | what is the effect of the Internet on student experiences on different types of students and what real gains there might be, if any, in replacing traditional teaching processes with new methods that exploit the Internet. | NA | N | 1 | 1 | 0 | 1 | 300 experimental students, 150 control | CS | NA | The sole use of internet for the instruction and communication of a distance course | Assessed for success with background questionnaires, learning style questionnaires, and final grades in the course | 2 | IDK | One group was offered the ability to take the same course completely via the internet (as opposed to assignments being sent via floppy disk in the mail) | Yes | "conventional" distance students who took the course in the same way it had been offered for years | N | final grade and preference for the conventional course or the internet course | continuous assessment and final exam scores for the computing class that they were taking | 2 | N | N | NA | N | N | The number of females in the internet population was slightly higher, not (statistically) significantly so, but the internet aspect of the course did not deter women from taking the course. Also age did not impact the willingness of students to take the internet-based or conventional course. No real difference in course outcomes was demonstrated by the conventional or the internet group. More methodic type learners preferred the conventional course and those who already used computers at their jobs preferred to take the internet course | None | They thought that women would be deterred from the internet group and they thought that younger people would be drawn to the internet group, but both were wrong. | N | NA | N | Only one course was offered, so this did not give a good image of how internet might affect other courses that are not already centered on computing. | N | Con/Neither, I think that the scope of this study is too small and it's too dated to offer much help. It basically says that people self select for internet use or not based on their comfort with using computers and their study type so it could be argued that those who have more methodical learning styles might not prefer to use internet-based learning and if they are required to it might hinder them, but the study didn't really go into the what-ifs. It might be difficult to extrapolate this data to other types of classes and to more modern forms of technology | 5 | 7 | N |
| Sam | SM-006 | 10/23/18 | Tech skills and wages | How do computerization and the use of internet effect wages of individuals?
|
THE LABOUR MARKET IN THE NEW
INFORMATION ECONOMY | By:Freeman, RB (Freeman, RB) | OXFORD REVIEW OF ECONOMIC POLICY
Volume: 18 Issue: 3 Pages: 288-305
Published:FAL 2002
Document Type:Article | DOI: 10.1093/oxrep/18.3.288 | Q2 | 1.444 | 36 | Yes | This article shows that computerization and use of the Internet are associated with greater hours worked as well as higher wages; that ICT occupations are rapidly increasing their share of employment; and, possibly most important of all, that trade unions have begun to use the Internet as a tool for servicing members and carrying their messages to the public, raising the possibility of a major change in the nature of the union movement. Quite relevant to the Sci Court case. | How do ICT and internet effect hours and wages? | They list hypothesis but I'm not sure they really relate to the study they did... it seems like they are just addressing related schools of thought | N | 1 | 0 | 1 | Study 1 | Census | Longitudinal | 12 years | The usage of ITCs and internet | Yes/no + some details reguarding the use | 5 | IDK | None | N | NA | N | | | | | | | | | | | | | | | | | Pro- This paper shows how computerization is associated with greater work hours and wages | 6 | 6 | N |
| Colin | CB-008 | 10/23/18 | Educational Impact | Print vs E-Textbook impact on performance | Electronic versus traditional print textbooks: A comparison study on the influence of university students’ learning | Rockinson-Szapkiw, A. J., Courduff, J., Carter, K., Bennett, D. | Computers & Education 63 (2013) 259–266 | 10.1016/j.compedu.2012.11.022 | Q1 | 4.538 | 77 | Yes | One important question that needs to be answered in deciding whether or not 1:1 technology is adopted is how e-textbooks compare to print textbooks in providing students with the knowledge and skills they need to succeed. Unfortunately, I haven't been able to dig up many experimental studies about K-12 learning, but there are some experiments with college students. | How does learning and performance compare when the primary vehicle for information dissemination is an e-textbook versus a print textbook? | NA | N | 1 | 0 | 1 | Study 1 | 538 | L | 1 Semester | Print vs E-textbook | Obvious | 5 | Y | None | N | NA | N | Grades, Self-Reported Learning | Standard classroom assessments and surveys | 4 | Y | Y | Demographic data, degree level, study habits (self-reported) | N | N | Print and e-textbooks were not different in terms of efficacy (grades/self-reported learning were the same across groups) | NA | NA | Y | They showed the two groups were homogeneous across the other measured variables listed on this sheet | Kind Of | SELECTION THREAT!
Few minority participants | Y | Pro: If e-textbooks are just as effective as print textbooks, and students report more positively on self-learning while using them, then the con side can't argue that they are a hinderance or that eye-fatigue and other complications affect performance. | 7 | 5 | N |
| Samantha | SV-006 | 10/23/18 | Educational Equity | How does mobile technology as an education tool affect the learning of English in non-native speakers? | m-Learning: An experiment in using SMS to support learning new English language words | Cavus, N (Cavus, Nadire)[ 1 ] ; Ibrahim, D (Ibrahim, Dogan)[ 2 ] | Nadire Cavus;Dogan Ibrahim, m-Learning: An experiment in using SMS to support learning new English language words, British journal of educational technology. , 2009, Vol.40(1), p.78-91 | 10.1111/j.1467-8535.2007.00801.x | Q1 | 2.729 | 145 | Yes | This article shows a different perspective other that the other sources I had been finding: this demonstrates that technology can work well with schools and can help non-native English speakers to be better students in technical areas | to find out the potential of using mobile phones in teaching new technical English language words to 1st-year undergraduate students to support their normal English language lectures. -- Does mobile technology in addition to regular second-language coursework help with retention? | They believe that yes, having continuous access to a mobile device and using it to supplement coursework will have a positive impact on the students' success | N | 1 | 1 | 0 | 1 | 45 first year undergraduate students in the Computer Information Systems program at Near East University (Turkey), volunteering to participate, non-native English speakers, students who already possess mobile phones (in 2007) | CS | NA | The sending of SMS definitions to students | pre and post assessment of understanding of definitions of English technical terms, using a Likert scale | 4 | Y | sending the SMS messages | N | NA | NA | success on pre and post assessment | pre and post assessment | 2 | N | N | NA | N | Y | "Results clearly indicate that before using the MOLT system, students had lower success rates than after using the MOLT system" | The hypothesis that having the SMS system helped the students to better learn the words was supported, however there was no control group so they should not be able to fully attribute the learning to the SMS system | NA | Y | They never offered any other kind of explanation or mention of why a control group was not used, they just said that the students used the SMS system and their scores went up therefore the scores are related to the use of the SMS system | Kind of | The authors listed the cost of the SMS sending system as a limitation. I think that the timing of the experiment was a limiting factor too because they mentioned that mobile devices might "one day" be used to review for tests by allowing students to take practice quizzes and learn more example problems from their mobile phones, but in 2007 the technology just wasn't there to facilitate that, nor could they really study the effectiveness of that. | Y | Pro: though it's dated and maybe tough to extrapolate to modern day, and though there was no control for native English speakers, their data does show that having the supplementary mobile technology can help students to learn a new language. | 7 | 3 | Y |
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
| COLOR CODING: Articles highlighed in blue are systematic reviews. Articles with a red X next to their ID were dropped at the pretrial review either due to arguments of relevance or scientific integrity. | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |