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Chih-Yueh Chou; Wei-Han Chen – Educational Technology & Society, 2025
Studies have shown that students have different help-seeking behavior patterns and tendencies and furthermore, that students with certain help-seeking behavior patterns and tendencies may have poor performance (i.e., at-risk students). This study applied an educational data mining approach, including clustering and classification, to analyze…
Descriptors: Student Behavior, Help Seeking, Problem Solving, Information Retrieval
Yamauchi, Taisei; Flanagan, Brendan; Nakamoto, Ryosuke; Dai, Yiling; Takami, Kyosuke; Ogata, Hiroaki – Smart Learning Environments, 2023
In recent years, smart learning environments have become central to modern education and support students and instructors through tools based on prediction and recommendation models. These methods often use learning material metadata, such as the knowledge contained in an exercise which is usually labeled by domain experts and is costly and…
Descriptors: Mathematics Instruction, Classification, Algorithms, Barriers
Jionghao Lin; Wei Tan; Lan Du; Wray Buntine; David Lang; Dragan Gasevic; Guanliang Chen – IEEE Transactions on Learning Technologies, 2024
Automating the classification of instructional strategies from a large-scale online tutorial dialogue corpus is indispensable to the design of dialogue-based intelligent tutoring systems. Despite many existing studies employing supervised machine learning (ML) models to automate the classification process, they concluded that building a…
Descriptors: Classification, Dialogs (Language), Teaching Methods, Computer Assisted Instruction
Jaurès S. H. Kameni; Bernabé Batchakui; Roger Nkambou – International Journal of Artificial Intelligence in Education, 2025
The majority of Sub-Saharan African countries are facing a very negative teacher-learner ratio: one teacher for over 120 learners. In order to support the learner training, we propose optimizing search engines for learning contexts, to enable learners to take optimal advantage of the vast reservoir of Open Educational Resources (OER) available on…
Descriptors: Foreign Countries, Teacher Shortage, Open Educational Resources, Computer Assisted Instruction
Kang, Hyeon-Ah; Han, Suhwa; Kim, Doyoung; Kao, Shu-Chuan – Educational and Psychological Measurement, 2022
The development of technology-enhanced innovative items calls for practical models that can describe polytomous testlet items. In this study, we evaluate four measurement models that can characterize polytomous items administered in testlets: (a) generalized partial credit model (GPCM), (b) testlet-as-a-polytomous-item model (TPIM), (c)…
Descriptors: Goodness of Fit, Item Response Theory, Test Items, Scoring
Missaoui, Siwar; Maalel, Ahmed – Education and Information Technologies, 2021
A student's profile defines the best way a student chooses to learn. It comprises information on student's characteristics such as background knowledge, learning style preference, goals, personality etc. The foremost challenge that the students experience in learning system is that they are unable to bring back relevant information based on their…
Descriptors: Profiles, Models, Computer Games, Cognitive Style
Gao, Ming; Zhang, Jingjing; Lu, Yu; Kahn, Ken; Winters, Niall – Journal of Computer Assisted Learning, 2023
Background: As a non-cognitive trait, grit plays an important role in human learning. Although students higher in grit are more likely to perform well on tests, how they learn in the process has been underexamined. Objectives: This study attempted to explore how students with different levels of grit behave and learn in an exploratory learning…
Descriptors: Resilience (Psychology), Academic Persistence, Personality Traits, Usability
Yuwono, Imam; Kusumastuti, Dewi Ekasari; Suherman, Yuyus; Zainudin; Dhafiya, Farah; Rahmatika, Puteri – Pegem Journal of Education and Instruction, 2023
This study aims to analyse the learning needs of college students with special needs, develop a Universal Design for Learning based learning application named AJAR MBK, and assess the efficiency of the AJAR MBK application. It used a research and development model adapted from the ADDIE (analysis, design, development, implementation, and…
Descriptors: Special Needs Students, Access to Education, Autism Spectrum Disorders, Material Development
Romadiah, Hikmah; Dayurni, Popi; Fajari, Laksmi Evasufi Widi – Online Submission, 2022
This research is motivated by the increasing number of users of android-based learning media it impacts the learning outcomes obtained. This study aims to determine the effect of android-based learning media on improving student learning outcomes. This research is a meta-analysis study. Data collection techniques are taken from indexing databases…
Descriptors: Meta Analysis, Handheld Devices, Telecommunications, Computer Assisted Instruction
Baosen Zhang; Ariana Frkonja-Kuczin; Zhong-Hui Duan; Aliaksei Boika – Journal of Chemical Education, 2023
Computer vision (CV) is a subfield of artificial intelligence (AI) that trains computers to understand our visual world based on digital images. There are many successful applications of CV including face and hand gesture detection, weather recording, smart farming, and self-driving cars. Recent advances in computer vision with machine learning…
Descriptors: Classification, Laboratory Equipment, Visual Aids, Optics
Development of a Computer Program for the Identification Key to Insect Orders (Arthropoda: Hexapoda)
Aydin, Gökhan; Duran, Volkan; Mertol, Hüseyin – International Journal of Curriculum and Instruction, 2021
This study aims to develop a computer program for the identification key to insect orders (Arthropoda: Hexapoda) and to investigate its effectiveness as teaching material. Secondly, this study is aiming at whether this program improves students' computational thinking skills or not longitudinal quasi-experimental design. Firstly, the study is…
Descriptors: Computer Software, Identification, Entomology, Computation
Zamborova, Katarina; Klimova, Blanka – Contemporary Educational Technology, 2023
The article presents the research of empirical mixed methods on the use of a modern mobile reading app compared to traditional forms of teaching in English business classes in higher education in Slovakia. The research belongs to the theoretical frame of the mobile assisted language learning field that has generated an interest since the early…
Descriptors: Business English, English for Special Purposes, Computer Software, Computer Assisted Instruction
Liu, Chenchen; Hwang, Gwo-Jen; Tu, Yun-fang; Yin, Yiqing; Wang, Youmei – Interactive Learning Environments, 2023
This study reviewed the mobile technology-supported music education (MTSME) studies published in several academic databases, namely Scopus, WOS, ERIC, and RILM, from 2008-2019. Based on the technology-based learning model, the application domains, research issues, sample groups, research methods, adopted devices, and learning strategies were…
Descriptors: Computer Assisted Instruction, Teaching Methods, Telecommunications, Handheld Devices
Lege, Ryan; Bonner, Euan – JALT CALL Journal, 2020
Virtual Reality (VR) has made significant inroads into both the consumer and professional sectors. As VR has matured as a technology, its overall practicality for use in education has also increased. However, due to the rapid evolution of the technology, the educational field struggles to stay informed of the latest advancements, changing…
Descriptors: Computer Simulation, Teaching Methods, Classification, Distance Education
Stephanie Link; Robert Redmon; Yaser Shamsi; Martin Hagan – CALICO Journal, 2024
Artificial intelligence (AI) for supporting second language (L2) writing processes and practices has garnered increasing interest in recent years, establishing AI-mediated L2 writing as a new norm for many multilingual classrooms. As such, the emergence of AI-mediated technologies has challenged L2 writing instructors and their philosophies…
Descriptors: English for Academic Purposes, Teaching Methods, Second Language Learning, Second Language Instruction