DEPARTMENT OF EDUCATION • NEHU, SHILLONG
M.A. III Semester
Unit II
Software Tools
Excel & SPSS
NVivo (Qualitative)
Mendeley
URKUND / Plagiarism
Presentation for Classroom Teaching — with Tool Walkthroughs
GETTING ORIENTED
Learning Outcomes
By the end of this session, you will be able to:
Use Excel & SPSS for quantitative data handling
Explain NVivo's role in qualitative analysis
Use Mendeley to manage references & citations
Explain plagiarism & how URKUND detects it
Appreciate UGC's academic-integrity framework
Know how to open & start using each tool
Introduction
Unit II — M.A. — Dept. of Education, NEHU
SECTION 2.0
Why These Tools Matter in Research
Every stage of research — managing data, analysing it, organising literature, and safeguarding originality — now relies on dedicated software.
Excel & SPSS
Quantitative data & analysis
NVivo
Qualitative data analysis
Mendeley
Reference management
URKUND
Plagiarism detection
Introduction
Unit II — M.A. — Dept. of Education, NEHU
2.2.1
Excel — Overview & Features
A spreadsheet application for entering, organising and doing preliminary analysis on quantitative data.
Grid of cells — rows = cases, columns = variables
Built-in functions: AVERAGE, MEDIAN, STDEV, COUNT...
Data Analysis ToolPak — correlation, t-tests, ANOVA
Sorting, filtering & conditional formatting
PivotTables & PivotCharts for quick summaries
Wide range of chart types for presenting data
Introduction to Excel
Unit II — M.A. — Dept. of Education, NEHU
2.2.2
Excel — Uses in Educational Research
1
Preparing a master data sheet from questionnaires/tests
2
Computing simple descriptive statistics for data screening
3
Creating tables, graphs & charts for reports and theses
4
Cleaning data before importing into SPSS
5
Maintaining record-keeping sheets & scoring keys
Excel and SPSS are usually used together: Excel for entry & cleaning, SPSS for advanced analysis.
Introduction to Excel
Unit II — M.A. — Dept. of Education, NEHU
2.2.3
Excel — How to Open & Use
1
Open Excel from Start Menu / Applications, or double-click an .xlsx file
2
Choose ‘Blank Workbook’, or File → Open for an existing file
3
Identify the Ribbon, Formula Bar, and the cell grid (columns A,B,C… rows 1,2,3…)
4
Click a cell to enter data, or type a formula starting with ‘=’
5
Use the Data tab for sorting, filtering & the Data Analysis ToolPak
6
Save regularly with Ctrl+S / Cmd+S in .xlsx format
Illustrative schematic only — not an actual screenshot of Microsoft Excel.
Introduction to Excel
Unit II — M.A. — Dept. of Education, NEHU
2.3.1
SPSS — Overview & Features
Dedicated statistical software with a menu-driven interface, extensively prescribed in Indian M.Ed./M.A. research courses.
1
Data View & Variable View — entry + variable definitions
2
Analyze menu: t-tests, ANOVA, correlation, regression…
3
Separate Output window (Viewer) for results
4
Syntax facility for reproducible analysis
5
Data transformation: recode, compute, split file
Introduction to SPSS
Unit II — M.A. — Dept. of Education, NEHU
2.3.2 & 2.3.3
SPSS — Working Procedure & Uses
WORKING PROCEDURE
USES IN RESEARCH
Introduction to SPSS
Unit II — M.A. — Dept. of Education, NEHU
2.3.4
SPSS — How to Open & Use
1
Open IBM SPSS Statistics, or double-click an existing .sav file
2
Choose ‘New Dataset’, or File → Open → Data (Excel/CSV also importable)
3
Define variables in Variable View — name, type, decimals, value labels
4
Enter/review data in Data View, one row per case, one column per variable
5
Choose a procedure from Analyze (e.g., Compare Means → T Test)
6
Review results in the Output window and copy relevant tables
Illustrative schematic only — not an actual screenshot of IBM SPSS Statistics.
Introduction to SPSS
Unit II — M.A. — Dept. of Education, NEHU
2.4.1
NVivo — Overview & Features
Qualitative Data Analysis (QDA) software for organising, coding & analysing rich, unstructured data.
Coding
Tag text with ‘nodes’ for themes
Memos
Record analytical reflections
Queries
Word-frequency & matrix coding
Visualisations
Word clouds, charts, models
Case Classification
Compare across sub-groups
Multi-format Support
Text, PDF, audio, video, images
Introduction to NVivo
Unit II — M.A. — Dept. of Education, NEHU
2.4.2
NVivo — Uses in Qualitative Educational Research
1
Systematically organising & coding large volumes of interview/focus-group data
2
Supporting thematic analysis, content analysis & grounded theory approaches
3
Facilitating comparison across participant categories (e.g., novice vs. experienced)
4
Maintaining an auditable record of how themes were developed — strengthening credibility
5
Supporting mixed-methods research alongside quantitative case attributes
Introduction to NVivo
Unit II — M.A. — Dept. of Education, NEHU
2.4.3
NVivo — How to Open & Use
1
Open NVivo, choose ‘New Project’ and give it a name
2
Import data as ‘Sources’ — transcripts, PDFs, documents, audio/video
3
Highlight a passage and create/apply a ‘Node’ (theme/concept code)
4
Continue coding; create new nodes as themes emerge
5
Use Memos to record analytical reflections as coding proceeds
6
Use Query tools (word frequency, matrix coding) to examine patterns
Illustrative schematic only — not an actual screenshot of NVivo.
Introduction to NVivo
Unit II — M.A. — Dept. of Education, NEHU
2.5.1
Mendeley — Overview & Features
A free reference manager that organises literature and auto-generates citations & bibliographies.
Personal library — store, organise & tag PDFs
Web Importer — capture references with one click
‘Cite While You Write’ plugin for MS Word
PDF annotation — highlight, note, comment
Group libraries for collaborative research
Cloud sync across multiple devices
Mendeley Reference Manager
Unit II — M.A. — Dept. of Education, NEHU
2.5.2
Mendeley — Using It in the Research Process
1
Import references while doing a literature review
2
Organise references into folders (by theme/chapter)
3
Insert in-text citations directly while writing
4
Auto-generate a formatted reference list
5
Switch citation style instantly if required (APA → MLA)
It doesn't replace careful reading & citation practice — but greatly reduces formatting errors in a thesis.
Mendeley Reference Manager
Unit II — M.A. — Dept. of Education, NEHU
2.5.3
Mendeley — How to Open & Use
1
Create a free Mendeley account; download Mendeley Reference Manager
2
Install the ‘Web Importer’ extension and ‘Cite While You Write’ plugin for Word
3
Click Web Importer while browsing Google Scholar/journal sites to add a reference
4
Organise your library into folders by chapter or theme
5
Use ‘Insert Citation’ in Word while writing to cite at the cursor
6
Use ‘Insert Bibliography’ to auto-generate the reference list
Illustrative schematic only — not an actual screenshot of Mendeley.
Mendeley Reference Manager
Unit II — M.A. — Dept. of Education, NEHU
2.6.1
Plagiarism — Concept & Types
Presenting someone else's ideas, words, data, or work as one's own, without proper acknowledgement.
Direct (Verbatim)
Copying text word-for-word, uncited
Paraphrasing
Rewording ideas closely, uncited
Mosaic (Patchwork)
Piecing together phrases from sources
Self-plagiarism
Reusing own past work undisclosed
Inadequate Citation
No quotation marks for direct quotes
Plagiarism Detection: URKUND
Unit II — M.A. — Dept. of Education, NEHU
2.6.2
URKUND — Features & Working
Sweden-based system, now Ouriginal (still called URKUND in Indian institutions). Screens theses & papers for textual overlap.
1
Document uploaded via institutional email integration or web portal
2
Compared against internet content, past papers & subscribed journals
3
Generates a similarity report — percentage + highlighted matches + sources
4
Researcher/supervisor reviews flagged passages for legitimate vs. problematic overlap
5
Document is revised — paraphrasing improved, citations added — before submission
Plagiarism Detection: URKUND
Unit II — M.A. — Dept. of Education, NEHU
2.6.3
URKUND — How Students Submit a Document
1
Log in to the plagiarism-check portal provided by your department/university
2
Upload the document (.doc, .docx, .pdf) via upload or drag-and-drop
3
Wait for processing — a full thesis may take a few minutes
4
Open the report to view overall similarity % and matched sources
5
Review flagged passages — revise via paraphrasing or add citations
6
Resubmit if required, until the report meets the prescribed threshold
Illustrative schematic only — not an actual screenshot of URKUND/Ouriginal.
Plagiarism Detection: URKUND
Unit II — M.A. — Dept. of Education, NEHU
2.6.4
UGC Regulations & Similarity Thresholds
UGC (Promotion of Academic Integrity & Prevention of Plagiarism) Regulations, 2018 govern research-degree submissions in India.
All M.Phil./Ph.D. theses must be checked for similarity — generally via software integrated with the INFLIBNET Shodhganga repository — before submission. Roughly 10% similarity (excluding quotations, references & generic terms) is generally regarded as acceptable, with escalating penalties for higher similarity levels.
Always verify the exact thresholds & penalty structure at your own institution — these may be revised or applied differently.
Plagiarism Detection: URKUND
Unit II — M.A. — Dept. of Education, NEHU
KEY TAKEAWAYS
Let Us Sum Up
1
Excel: data entry, cleaning, basic stats & tabular/graphical presentation
2
SPSS: menu-driven statistical software for descriptive & inferential analysis
3
NVivo: coding, memos, queries & visualisation of qualitative/multimedia data
4
Mendeley: reference library with automatic citation & bibliography generation
5
URKUND (Ouriginal): similarity checking, used per UGC academic-integrity rules
Summary
Unit II — M.A. — Dept. of Education, NEHU
Let's Discuss
For your own dissertation topic, which of these five tools would you rely on most — and at which stage of the research process would you use each one?
Self-Check Exercises — see accompanying study material, Section 2.8
Discussion
Unit II — M.A. — Dept. of Education, NEHU