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Allan Jeong; Hyoung Seok-Shin – International Association for Development of the Information Society, 2023
The Jeong (2020) study found that greater use of backward and depth-first processing was associated with higher scores on students' argument maps and that analysis of only the first five nodes students placed in their maps predicted map scores. This study utilized the jMAP tool and algorithms developed in the Jeong (2020) study to determine if the…
Descriptors: Critical Thinking, Learning Strategies, Concept Mapping, Learning Analytics
Sami Baral; Eamon Worden; Wen-Chiang Lim; Zhuang Luo; Christopher Santorelli; Ashish Gurung; Neil Heffernan – Grantee Submission, 2024
The effectiveness of feedback in enhancing learning outcomes is well documented within Educational Data Mining (EDM). Various prior research have explored methodologies to enhance the effectiveness of feedback to students in various ways. Recent developments in Large Language Models (LLMs) have extended their utility in enhancing automated…
Descriptors: Automation, Scoring, Computer Assisted Testing, Natural Language Processing
Chanchal, Akchunya; Zualkernan, Imran – International Association for Development of the Information Society, 2022
Systematic classroom observation is often used in evaluating and enhancing the quality of classroom instruction. However, classroom observation can potentially suffer from human bias. In addition, the traditional classroom observation is too expensive for resource-constrained environments (e.g., Sub-Saharan Africa, South and Central Asia). A…
Descriptors: Audio Equipment, Classroom Observation Techniques, Cost Effectiveness, Educational Quality
Ji-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Grantee Submission, 2022
This paper demonstrates how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. We examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance prediction; and (2) what types of in-game features were associated with student…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
Garbarino, Jennifer J. – 1996
All parametric analysis focuses on the "synthetic" variables created by applying weights to "observed" variables, but these synthetic variables are called by different names across methods. This paper explains four ways of computing the synthetic scores in factor analysis: (1) regression scores; (2) M. S. Bartlett's algorithm…
Descriptors: Algorithms, Factor Analysis, Regression (Statistics), Scores
Kurz, Terri Barber – 1999
Multiple-choice tests are generally scored using a conventional number right scoring method. While this method is easy to use, it has several weaknesses. These weaknesses include decreased validity due to guessing and failure to credit partial knowledge. In an attempt to address these weaknesses, psychometricians have developed various scoring…
Descriptors: Algorithms, Guessing (Tests), Item Response Theory, Multiple Choice Tests
Ackerman, Terry A. – 1991
This paper examines the effect of using unidimensional item response theory (IRT) item parameter estimates of multidimensional items to create weakly parallel test forms using target information curves. To date, all computer-based algorithms that have been devised to create parallel test forms assume that the items are unidimensional. This paper…
Descriptors: Algorithms, Equations (Mathematics), Estimation (Mathematics), Item Response Theory