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Austin M. Shin; Ayaan M. Kazerouni – ACM Transactions on Computing Education, 2024
Background and Context: Students' programming projects are often assessed on the basis of their tests as well as their implementations, most commonly using test adequacy criteria like branch coverage, or, in some cases, mutation analysis. As a result, students are implicitly encouraged to use these tools during their development process (i.e., so…
Descriptors: Feedback (Response), Programming, Student Projects, Computer Software
Chattoe-Brown, Edmund – International Journal of Social Research Methodology, 2023
This article argues that Agent-Based Modelling, owing to its capabilities and methodology, has a distinctive contribution to make to delivering coherent social science prediction. The argument has four parts. The first identifies key elements of social science prediction induced from real research across disciplines, thus avoiding a straw person…
Descriptors: Futures (of Society), Models, Evaluation Methods, Social Science Research
Hyemin Yoon; HyunJin Kim; Sangjin Kim – Measurement: Interdisciplinary Research and Perspectives, 2024
We have maintained the customer grade system that is being implemented to customers with excellent performance through customer segmentation for years. Currently, financial institutions that operate the customer grade system provide similar services based on the score calculation criteria, but the score calculation criteria vary from the financial…
Descriptors: Classification, Artificial Intelligence, Prediction, Decision Making
Xieling Chen; Haoran Xie; Di Zou; Lingling Xu; Fu Lee Wang – Educational Technology & Society, 2025
In massive open online course (MOOC) environments, computer-based analysis of course reviews enables instructors and course designers to develop intervention strategies and improve instruction to support learners' learning. This study aimed to automatically and effectively identify learners' concerned topics within their written reviews. First, we…
Descriptors: Classification, MOOCs, Teaching Skills, Artificial Intelligence
Du, Han; Enders, Craig; Keller, Brian; Bradbury, Thomas N.; Karney, Benjamin R. – Grantee Submission, 2022
Missing data are exceedingly common across a variety of disciplines, such as educational, social, and behavioral science areas. Missing not at random (MNAR) mechanism where missingness is related to unobserved data is widespread in real data and has detrimental consequence. However, the existing MNAR-based methods have potential problems such as…
Descriptors: Bayesian Statistics, Data Analysis, Computer Simulation, Sample Size
Bogdan Nicula; Mihai Dascalu; Tracy Arner; Renu Balyan; Danielle S. McNamara – Grantee Submission, 2023
Text comprehension is an essential skill in today's information-rich world, and self-explanation practice helps students improve their understanding of complex texts. This study was centered on leveraging open-source Large Language Models (LLMs), specifically FLAN-T5, to automatically assess the comprehension strategies employed by readers while…
Descriptors: Reading Comprehension, Language Processing, Models, STEM Education
Mario Vallarino; Saverio Iacono; Edoardo Bellanti; Gianni V. Vercelli – IEEE Transactions on Learning Technologies, 2024
This article introduces a novel approach to remote laboratory instruction, specifically designed for teaching three-dimensional modeling using Blender software. The lab uses virtual machines to provide students with the necessary computational power to carry out the course activities, along with the correct version of the software. The flipped…
Descriptors: Flipped Classroom, Distance Education, Laboratories, Peer Evaluation
Yun Long; Haifeng Luo; Yu Zhang – npj Science of Learning, 2024
This study explores the use of Large Language Models (LLMs), specifically GPT-4, in analysing classroom dialogue--a key task for teaching diagnosis and quality improvement. Traditional qualitative methods are both knowledge- and labour-intensive. This research investigates the potential of LLMs to streamline and enhance this process. Using…
Descriptors: Classroom Communication, Computational Linguistics, Chinese, Mathematics Instruction
Achter, Sebastian; Borit, Melania; Chattoe-Brown, Edmund; Siebers, Peer-Olaf – International Journal of Social Research Methodology, 2022
This article describes and justifies a reporting standard to improve data use documentation in Agent-Based Modelling. Following the development of reporting standards for models themselves, empirical modelling has now developed to the point where these standards need to take equally effective account of data use (which previously has tended to be…
Descriptors: Data Use, Data Analysis, Models, Usability
Qiuyu Zheng; Zengzhao Chen; Mengke Wang; Yawen Shi; Shaohui Chen; Zhi Liu – IEEE Transactions on Learning Technologies, 2024
The rationality and the effectiveness of classroom teaching behavior directly influence the quality of classroom instruction. Analyzing teaching behavior intelligently can provide robust data support for teacher development and teaching supervision. By observing verbal and nonverbal behaviors of teachers in the classroom, valuable data on…
Descriptors: Teacher Behavior, Teacher Student Relationship, Verbal Communication, Nonverbal Communication
Katia Ciampa; Zora Wolfe; Meagan Hensley – Technology, Pedagogy and Education, 2025
This study explores the role of artificial intelligence (AI) in K-12 student assessment practices, focusing on educators' use of AI tools. Through content analysis of active Facebook groups dedicated to AI in education, the authors examined how educators integrate AI into assessment across various grade levels and subjects. Using the Technology…
Descriptors: Artificial Intelligence, Computer Software, Technology Integration, Kindergarten
Picones, Gio; PaaBen, Benjamin; Koprinska, Irena; Yacef, Kalina – International Educational Data Mining Society, 2022
In this paper, we propose a novel approach to combine domain modelling and student modelling techniques in a single, automated pipeline which does not require expert knowledge and can be used to predict future student performance. Domain modelling techniques map questions to concepts and student modelling techniques generate a mastery score for a…
Descriptors: Prediction, Academic Achievement, Learning Analytics, Concept Mapping
Chung, Seungwon; Houts, Carrie – Measurement: Interdisciplinary Research and Perspectives, 2020
Advanced modeling of item response data through the item response theory (IRT) or item factor analysis frameworks is becoming increasingly popular. In the social and behavioral sciences, the underlying structure of tests/assessments is often multidimensional (i.e., more than 1 latent variable/construct is represented in the items). This review…
Descriptors: Item Response Theory, Evaluation Methods, Models, Factor Analysis
Robertson, Royce L.; Larki, Martha J. – Journal of Educational Research and Practice, 2019
Maturity models fill the need for a measure of overall growth in how outcomes assessment is defined and how feedback informs improvement to meet internal and external expectations at individual institutions of higher education. An exploratory qualitative study was conducted to develop an instrument, the Assessment System Maturity Matrix (ASMM), to…
Descriptors: Feedback (Response), Higher Education, Evaluation Methods, Computer Software
Boxuan Ma; Sora Fukui; Yuji Ando; Shinichi Konomi – Journal of Educational Data Mining, 2024
Language proficiency diagnosis is essential to extract fine-grained information about the linguistic knowledge states and skill mastery levels of test takers based on their performance on language tests. Different from comprehensive standardized tests, many language learning apps often revolve around word-level questions. Therefore, knowledge…
Descriptors: Language Proficiency, Brain Hemisphere Functions, Language Processing, Task Analysis