Correlations and Tradeoffs Between Courses and Cognitive Skills

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Srivastava, Siddharth
Prabhakar, T V
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Commonwealth of Learning (COL)
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In online education, it is often not possible to assess the suitability of a course for a particular student. We need a handle on how to decide if a student is ready to do a course. This research is aimed at arriving a framework for doing so. // Courses have been identified to fall under four categories viz. Logic Intensive (LogI), Numerical Computation Intensive (NumI), Memory Intensive (MemI) and Application Intensive (AppI). For example, Programming would be classified as LogI, Linear Algebra as NumI, Management Information Systems as MemI and Projects would be AppI. // The data is gathered through a questionnaire and standard tests for IQ, Emotional Quotient, Mental Age, Left/Right brain scores. The students were from National-P.G. College, Lucknow, India. // Data obtained is subjected to K-Means algorithm (with K=3) resulting in three clusters - High, Moderate, and Low performing students. Each cluster was further analyzed concerning course categories and cognitive score using correlation analysis. We calculated pair-wise correlations between the performance of students in the various categories. One example observation is High correlation of LogI with MemI and AppI. That means students who performed well in LogI type courses also did well in MemI and AppI courses. // Our next investigation is based on Blooms Taxonomy we compute correlations between Course Category and Lower-Level skill in the Cognitive domain. Based on scores achieved in each Category, we construct a strength-vector for each student indicating what subjects they scored best. The strength-vector for High-performance students is {LogI, NumI, MemI, AppI} whereas for Low-performance students it is {AppI, MemI, LogI, NumI}. High and Low-performance students are left and right-brain dominant, respectively. Moderate-performance students have balanced brain dominance. This aligns with well-known theories of the brain. We believe an understanding of this kind will enable online educators to design appropriate courses for their audience. // Paper ID 145
Massive Open Online Courses (MOOC), Curriculum Planning, Technology and Innovation