The book defines analytics-based feedback in the context of learning analytics in education and offers methodology-specific guidance to conduct experimental research in the field of educational data science. It focuses not only on developing a technique but also the benefits of learning analytics in school level education.
In a rapidly evolving and expanding world around big data and data science, there is a need to focus on apposite training and advancing knowledge economy to strengthen its utility. It will meet the future needs to devise learning analytics to improve student performance and learning outcomes. It will be useful for the working professionals in the ed-tech field who are keen to implement data science in education sector.
The book contributes to the data science in education through research-based experience and understanding of ideas such as learning analytics and analytics-based feedback to improve academic performances and learning outcomes. It may be useful for learners, scholars and all the stake holders having interest in the subject.
Dr. Deepti Yadav is an Assessment Expert consultant with Australian Council for Educational Research (ACER), India. Formerly, an Associate Research Scientist at Kaplan, Bangalore, Assistant Professor at Regional Institute of Education, NCERT, Bhopal with a Post Graduate Program in Data Science and Business Analytics certificate from McCombs School of Business, Texas, University Grants Commission’s senior research fellow. Dr Deepti is an international storyteller, script writer, and translator, her research endeavors are for transforming education with data science and analytics-based actionable insights.
The Analogical Foreground
Acknowledgements
1. Learning Analytics: Concept and importance/ 1
Analytics / 2; Learning Analytics — Concept and Definition / 3; Brief History of Analytics and Learning Analytics / 3; Importance / 6; Components / 7; Learning Analytics for School / 9; Learning Analytics and Analytics-Based Feedback / 9; Analytics-Based Feedback (AbF) / 10; Summary and Suggestions / 11
2. Language Teaching-Learning and Learning Analytics/ 12
Learning Analytics for English Language-Learning / 12; Language-Learning / 13; English Language Teaching in India / 21; Conceptual Framework / 24; Stakeholders of the Study / 27; Other Components / 28; Summary and Conclusion / 32
3. Rationale with Literature Review: Learning Analytics/ 33
Learning Analytics / 33; Feedback with Learning Analytics / 49; Learning Analytics in School / 56
4. Learning Analytics, Language and Other Components: Literature Review/ 65
Learning Analytics and Language / 65; Learning Analytics and Motivation / 71; Language and Other Variables / 75
5. Learning Analytics Scenario — India vis-a-vis World: Rationale with Literature Review/ 98
Global Research Developments related to AbF since Covid-19 / 98; Research Developments in India related to Learning Analytics / 100; Rationale of the Study / 102; Summary and Conclusion / 108
6. The Study Essentials/ 109
Statement of the Problem / 109; Research Questions / 109; Objectives / 110; Hypotheses / 111; Delimitations / 111
7. Methodology and Approach/ 112
Methodology / 112; Tools Used / 115; Procedure of Data Collection / 123; Statistical Techniques Used for Data Analysis / 124
8. Data Analysis, Results and Findings/ 126
Effectiveness of Analytics-Based Feedback in Terms of Descriptive Analysis / 126; Trend of Effect of the Treatment on BICS Component of Achievement in English Language / 129; Trend of Effect of the Treatment on CALP Component of Achievement / 131; Trend of Effect of the Treatment on Overall Achievement / 133; Relationship between BICS Component of Achievement in English Language Progression and the Treatment, Gender, Socio-economic Status and Learning Style / 135; Relationship between CALP Component of Achievement in English Language Progression and the Treatment / 137; Relationship between Overall Achievement in English Language Progression and the Treatment / 139; Effect of Treatment and Interactive Effect of the Treatment and Gender on Study Habits by Taking the Pre-Test Scores of Study Habit as a Covariate / 140; Effect of Treatment and Interactive Effect of Treatment and Gender on the Attitude / 143; Effect of Treatment and Interactive Effect of Treatment and Gender on the Motivation Level of Students When Measured with MSLQ / 145; Effectiveness of Analytics-based Feedback in Terms of Qualitative Aspect / 147; Issues and Challenges Related to Conducting Learning Analytics Study in India / 151
9. Research Discussions, Implications and Suggestions/ 155
Objective-wise Major Findings / 155; Interpretation of Results and Discussion / 157; Implications of the Study / 171; Suggestions for Further Studies / 174
Bibliography/ 177