Book Chapter10.1007/978-3-030-23204-7_26
Annotated Examples and Parameterized Exercises: Analyzing Students’ Behavior Patterns
Mehrdad Mirzaei,Shaghayegh Sahebi,Peter Brusilovsky +2 more
- 25 Jun 2019
- pp 308-319
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TL;DR: This work model student behavior in the form of vectors of micro-patterns and examine student behavior stability in various ways via these vectors to discover and examine global behavior patterns associated with groups of students.
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Abstract: Recent studies of student problem-solving behavior have shown stable behavior patterns within student groups. In this work, we study patterns of student behavior in a richer self-organized practice context where student worked with a combination of problems to solve and worked examples to study. We model student behavior in the form of vectors of micro-patterns and examine student behavior stability in various ways via these vectors. To discover and examine global behavior patterns associated with groups of students, we cluster students according to their behavior patterns and evaluate these clusters in accordance with student performance.
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Citations
Gamification in education: a mixed-methods study of gender on computer science students’ academic performance and identity development
Leila Zahedi,Jasmine Skye Batten,Monique S. Ross,Geoff Potvin,Stephanie Damas,Peter Clarke,Debra Davis +6 more
TL;DR: SEP-CyLE is introduced, an online gamified tool designed to provide supplemental computing content to students and shows that virtual points and the leaderboard contributed to improved performance for students of all genders, suggesting that gamification is a gender-neutral learning engagement strategy that improves female students' performance as much as male students.
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Understanding Weekly COVID-19 Concerns through Dynamic Content-Specific LDA Topic Modeling
Mohammadzaman Zamani,H. Andrew Schwartz,Johannes C. Eichstaedt,Sharath Chandra Guntuku,Adithya V Ganesan,Sean A. P. Clouston,Salvatore Giorgi +6 more
- 01 Nov 2020
TL;DR: This work proposes a dynamic content-specific LDA topic modeling technique that can help to identify different domains of COVID-specific discourse that can be used to track societal shifts in concerns or views and shows that these model-derived topics are more coherent than standard LDA topics.
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•Proceedings Article
Rank-Based Tensor Factorization for Student Performance Prediction.
Thanh-Nam Doan,Shaghayegh Sahebi +1 more
- 01 Jan 2019
TL;DR: This paper proposes a tensor factorization model for student performance prediction that does not rely on a predefined domain model, and models student knowledge as a soft membership of latent concepts in the knowledge acquisition process.
Automatic Content Analysis of Student Moral Discourse in a Collaborative Learning Activity
Claudio Alvarez,Gustavo Zurita,Andrés Carvallo,Pablo Ramírez,Eugenio Bravo,Nelson Baloian +5 more
- 31 Aug 2021
TL;DR: In this paper, the authors present a solution to the problem, based on enhancing EthicApp's teacher's interface with automated content analysis capabilities, including a dashboard that automatically displays students' most relevant contributions, and cluster visualizations that permit identifying groups of students with similar responses to activity tasks.
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Structure-Based Discriminative Matrix Factorization for Detecting Inefficient Learning Behaviors
Mehrdad Mirzaei,Shaghayegh Sahebi,Peter Brusilovsky +2 more
- 01 Dec 2020
TL;DR: In this paper, a structure-based discriminative non-negative matrix factorization model is proposed to distinguish between common and distinct learning behavior patterns of low and high learning gain students.
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