Machine Learning Techniques to Evaluate Lesson Objectives

Cher, Pei Hua; Lee, Jason Wen Yau; Bello, Fernando

doi:10.1007/978-3-031-11644-5_16

Cited by 2 publications

(1 citation statement)

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“…Different approaches are used in the literature for extracting features from the free-form educational text, such as Word2Vec (Mikolov et al 2013), Glove (Pennington, Socher, and Manning 2014), and more recently, transformerbased model BERT. BERT and its variation S-BERT is used for many educational tasks such as analyzing surveys (Esmaeilzadeh et al 2022), evaluation of students' essays and exams (Cochran et al 2022;Padó 2022;Condor, Litster, and Pardos 2021), lecture summarization (Miller 2019), and evaluating lesson objectives (Cher, Lee, and Bello 2022).…”

Section: Contextual Embeddingmentioning

confidence: 99%

Context-Aware Analysis of Group Submissions for Group Anomaly Detection and Performance Prediction

Norouzi

Mazaheri

2023

AAAI

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Learning exercises that activate students’ additional cognitive understanding of course concepts facilitate contextualizing the content knowledge and developing higher-order thinking and problem-solving skills. Student-generated instructional materials such as course summaries and problem sets are amongst the instructional strategies that reflect active learning and constructivist philosophy. The contributions of this work are twofold: 1) We introduce a practical implementation of inside-outside learning strategy in an undergraduate deep learning course and will share our experiences in incorporating student-generated instructional materials learning strategy in course design, and 2) We develop a context-aware deep learning framework to draw insights from the student-generated materials for (i) Detecting anomalies in group activities and (ii) Predicting the median quiz performance of students in each group. This work opens up an avenue for effectively implementing a constructivism learning strategy in large-scale and online courses to build a sense of community between learners while providing an automated tool for instructors to identify at-risk groups.

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