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SESSION:
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COURSE AND CODE NAME:
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CLUSTER 3c RUBRIC: DIGITAL & NUMERACY SKILLS
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DIGITAL & NUMERACY SKILLSTOTAL
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DATA COLLECTIONTOTALMODEL APPLICATIONTOTALDATA MANIPULATIONTOTALINTERPRETATIONTOTALPROBLEM SOLVINGTOTALOUTPUT / RESULTSTOTAL
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EXCELLENT (9-10)GOOD (7-8)SATISFACTORY (5-6)FAIR (3-4)POOR (1-2)EXCELLENT (9-10)GOOD (7-8)SATISFACTORY (5-6)FAIR (3-4)POOR (1-2)EXCELLENT (9-10)GOOD (7-8)SATISFACTORY (5-6)FAIR (3-4)POOR (1-2)EXCELLENT (9-10)GOOD (7-8)SATISFACTORY (5-6)FAIR (3-4)POOR (1-2)EXCELLENT (9-10)GOOD (7-8)SATISFACTORY (5-6)FAIR (3-4)POOR (1-2)EXCELLENT (9-10)GOOD (7-8)SATISFACTORY (5-6)FAIR (3-4)POOR (1-2)
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•Excellently use of digital application, thus seeking of descriptions of different data types or scales entirely appropriate.
•Able to differentiate or define between original and derived data with 0 or 1 mistake.		•Good use of digital application, thus seeking of descriptions of different data types or scales mostly appropriate.
•Able to differentiate or define between original and derived data with 2 or 3 mistakes.		•Satisfactorily use of digital application, thus seeking of descriptions of different data types or scales sometimes appropriate.
•Able to differentiate or define between original and derived data with 4 or 5 mistakes.		•Fairly use of digital application, thus seeking of descriptions of different data types or scales rarely appropriate.
•Able to differentiate or define between original and derived data with 6 or 7 mistakes.		•Poorly use of digital application, thus seeking of descriptions of different data types or scales very rarely appropriate.
•Able to differentiate or define between original and derived data with 8 or more mistakes.		•Able to recognize, select and apply appropriate model# for the situation with high competency level.
•Excellent familiarization with knowledge and understanding of the range of model# available.		•Able to recognize, select and apply appropriate model# for the situation with above average competency level.
•Above average knowledge and understanding of the range of model# available.		•Able to recognize, select and apply appropriate model# for the situation with moderate competency level.
•Average knowledge and understanding of the range of model# available.		•Able to recognize, select and apply appropriate model# for the situation with minimum competency level.
•Limited knowledge or understanding of the range of model# available.		•Failure to recognize, select and apply appropriate model# for the situation due to no competency.
•Little knowledge or understanding of the range of model# available.		•Expertly perform data manipulations and organize data into graphic/numeric/text forms as per task requirements.
•Show ability to construct complex data displays^ from set of data.
•Always able to distinguish the range of data available.		•Competently perform data manipulations and organize data into graphic/numeric/text forms as per task requirements.
•Show ability to construct complete data displays^ from set of data.
•Usually able to distinguish the range of data available.		•Moderately perform data manipulations and organize data into graphic/numeric/text forms as per task requirements.
•Show ability to construct data displays^ from set of data.
•Sometimes able to distinguish between the range of data available.		•Fairly perform data manipulations and organize data into graphic/numeric/text forms as per task requirements.
•Show ability to construct simple data displays^ from set of data.
•Rarely able to distinguish between the range of data available.		•Hardly perform data manipulations or organize data into graphic/numeric/text forms as per task requirements.
•Show inability to construct any data displays^ from set of data.
•Very rarely able to distinguish between the range of data available.
•Make more than 3 inferences consistent with all data displays^ lead to much better understanding.
•Explain clearly in own language the meaning of the data and relate it to accurate context.		•Make 3 inferences consistent with most data displays^ lead to better understanding.
•Explain the meaning of the data and relate it to appropriate context.		•Make 2 inferences consistent with some data displays^ lead to moderate understanding.
•Explain the inferences within a suitable context.		•Make 1 inference consistent with few data displays^ lead to minimum understanding.
•Explain the inferences within a limited context.		•Make no (0) inference consistent with any data displays^ lead to misunderstanding.
•Explain the inferences without appropriate context.		•Very frequently identify and apply appropriate format+ to solve problems.
•Attain more than 89% of format accuracy in problem solving.		•Frequently identify and apply appropriate format+ to solve problems.
•Attain between 80% and 89% of format accuracy in problem solving.
•Sometimes identify and apply appropriate format+ to solve problems.
•Attain between 70% and 79% of format accuracy in problem solving.
•Occasionally identify and apply appropriate format+ to solve problems.
•Attain between 60% and 69% of format accuracy in problem solving.		•Never identify and apply appropriate format+ to solve problems.
•Attain less than 60% of format accuracy in problem solving.		•Produce excellent and high quality of output with more than 89 of accuracy of final answers (facts and figures).
•Overall results indicate high level of digital and numerical skills.		•Produce good quality of output between 80% and 89% of accuracy of final answers (facts and figures).
•Overall results indicate slightly high level of digital and numerical skills. 		•Produce satisfactory quality of output between 70% and 79% of accuracy of final answers (facts and figures).
•Overall results indicate average level of digital and numerical skills. 		•Produce fair quality of output between 60% and 69% of accuracy of final answers (facts and figures).
•Overall results indicate slightly low level of digital and numerical skills.
•Produce poor quality of output with less than 60% of accuracy of final answers (facts and figures).
•Overall results indicate low level of digital and numerical skills.
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No.Registration No.Name10%10%10%10%20%20%20%20%20%20%20%20%100%COMMENTS
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1101010101020102010201020100
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20099918816102091881
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3008891881691891878
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49999816816091868
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50088816816091858
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68899816816091867
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77799918816091868
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84488816816091862
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92299918816091863
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10088816816091858
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11088816816091858
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12088816816091858
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13099816816091859
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14099816816091859
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15088816816091858
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16099816816091859
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17099816816091859
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18099816816091859
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198899816918091869
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20088816816091858
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21088816816091858
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22088816816091858
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23088816816091858
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24099816816091859
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25099816816091859
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26088816918091860
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27099918816091861
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28088816816091858
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29088816816091858
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30088816816091858
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31088816816091858
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32088816816091858
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33088816816091858
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34088816816091858
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35088816816091858
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36088816816091858
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37088816816091858
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38088816816091858
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39088816816091858
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40088816816091858
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41088816816091858
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42088816816091858
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43088816816091858
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44088816816091858
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45088816816091858
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46088816816091858
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47088816816091858
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48088816816091858
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49088816816091858
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50088816816091858
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