Applicability of Educational Data Mining in Afghanistan: Opportunities and Challenges
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The document discusses the applicability of educational data mining (EDM) in Afghanistan, highlighting the opportunities and challenges in utilizing this emerging discipline to improve educational outcomes. It identifies the potential benefits of EDM, such as advising students on major selection, predicting at-risk students, and enhancing institutional performance, but notes significant obstacles like inadequate data accessibility and a lack of expertise in data mining. The paper underscores the need for better data management in Afghan education systems to leverage EDM effectively.
Applicability of Educational Data Mining in Afghanistan: Opportunities and Challenges
- 1. 1 1. https://www.researchgate.net/publication/314942684_Applicability_of_Educatio nal_Data_Mining_in_Afghanistan_Opportunities_and_Challenges 2. http://www.educationaldatamining.org/EDM2016/proceedings/paper_1.pdf For more information read the following papers:
- 2. Applicability of Educational Data Mining in Afghanistan: Opportunities and Challenges Abdul Rahman Sherzad Lecturer at Computer Science Faculty of Herat University, Afghanistan Ph.D. Student at Technische Universität Berlin, Germany October 11, 2016 (Technische Universität Berlin)
- 3. The Key Terms Data Mining Educational Data Mining (EDM) EDM Applications EDM in Afghanistan 3
- 5. Data Mining Data Mining Explain the past Exploration Techniques Predict the future Modeling Techniques 5
- 6. Educational Data Mining It is an emerging discipline to develop methods for exploring the data that come from educational settings to better understand students and the settings which they learn in. 6
- 7. EMD Application EDM is useful in many different areas including • Providing feedback for supporting instructors, • Detecting undesirable student behaviors, • identifying at-risk students, • increasing graduation rates, • effectively evaluating institutional performance, • recommending the right courses for the students, • and helping students in Major selection. 7
- 8. 1. Does Afghanistan Education Systems need EMD? In the context of Afghanistan, ◦ there are large amounts of data available for mining purposes in the education domain, ◦ but the methods that the educational institutions use to store and produce their data only enable them to achieve basic insights. 2. What are the EDM Applicability in Afghanistan Education Systems? 8
- 9. Transaction of schools data in Afghanistan (scenario) General education students facts # of students years of study # of subjects (average) exams (mid and final) Total Records ~ 10,000,000 9 13 2 2,340,000,000 9 NOTE: The above-mentioned calculations indicate (only) marks data. Of course there are different entities exist in the university and school systems i.e. teachers, students, students dependents, subjects, activities, classes, etc. Public High school students facts # of students years of study # of subjects (average) exams (mid and final) Total Records ~ 1,000,000 3 15 2 90,000,000 Public High school graduates/year facts # of students years of study # of subjects (average) exams (mid and final) Total Records ~ 200,000 3 15 2 18,000,000
- 10. Storage of schools data in Afghanistan (scenario) Primary & Secondary schools data storage (estimation) # of students Storage/student Total Storage (MB) Total Storage (GB) Total Storage (TB) ~ 10,000,000 2 MB 20,000,000 MB 20,000 GB 20 TB 10 NOTE: Consider how much data is generated/day (explicitly, implicitly) when there are Learning Management Systems (LMSs) available at schools and universities! High schools data storage (estimation) # of students Storage/student Total Storage (MB) Total Storage (GB) Total Storage (TB) ~ 1,000,000 2 MB 2,000,000 MB 2,000 GB 2 TB
- 11. The Problem Inappropriate choice of Major ◦ students are not offered specialized studies at high schools, ◦ family literacy rates are low so parents cannot help students with choosing a career, ◦ high schools lack basic career counseling services, ◦ and there are no academic advisory organizations outside educational institutions to guide the students on this critical career decision. 11 NOTE: The data shows one-third of the students admitted into Herat public university could not continue higher education studies!
- 12. EDM Application I: Major prediction 12 In Afghanistan, there are no academic advisory organizations to guide the Kankor candidates on choosing proper fields of study. • Design a classification model to predict/recommend proper Major to high school graduates prior attending the Kankor. In Afghanistan, students are not offered specialized studies. • Design a learning model to automate student placement into sciences or social sciences while specialized studies is offered at school level.
- 13. EDM Application II: Support student at risk of attrition and failure 13 In Afghanistan, most of the students have no knowledge of the requirements and prerequisites of the offered fields of study, and select randomly. ◦ The results are poor performance or high rates of dropout in higher education.
- 14. Challenges prevent the applicability of EDM in Afghanistan • Lack of data availability and accessibility! • Lack of experts in the domain of Data Mining and Educational Data Mining! 14
- 15. 15 1. https://www.researchgate.net/publication/314942684_Applicability_of_Educatio nal_Data_Mining_in_Afghanistan_Opportunities_and_Challenges 2. http://www.educationaldatamining.org/EDM2016/proceedings/paper_1.pdf For more information read the following papers: