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Pejic, Marko; Savic, Goran; Segedinac, Milan – Journal of Educational Computing Research, 2021
This study proposes a software system for determining gaze patterns in on-screen testing. The system applies machine learning techniques to eye-movement data obtained from an eye-tracking device to categorize students according to their gaze behavior pattern while solving an on-screen test. These patterns are determined by converting eye movement…
Descriptors: Eye Movements, Computer Assisted Testing, Computer Software, Evaluation Methods
Smith, Glenn Gordon; Haworth, Robert; Žitnik, Slavko – Journal of Educational Computing Research, 2020
We investigated how Natural Language Processing (NLP) algorithms could automatically grade answers to open-ended inference questions in web-based eBooks. This is a component of research on making reading more motivating to children and to increasing their comprehension. We obtained and graded a set of answers to open-ended questions embedded in a…
Descriptors: Natural Language Processing, Computer Assisted Testing, Grading, Electronic Publishing
An Investigation of High School Students' Errors in Introductory Programming: A Data-Driven Approach
Qian, Yizhou; Lehman, James – Journal of Educational Computing Research, 2020
This study implemented a data-driven approach to identify Chinese high school students' common errors in a Java-based introductory programming course using the data in an automated assessment tool called the Mulberry. Students' error-related behaviors were also analyzed, and their relationships to success in introductory programming were…
Descriptors: High School Students, Error Patterns, Introductory Courses, Computer Science Education

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