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Chi Hong Leung; Winslet Ting Yan Chan – Asian Journal of Contemporary Education, 2025
This paper explores the efficacy of ChatGPT, a generative artificial intelligence in educational contexts, particularly concerning its potential to assist students in overcoming academic challenges while highlighting its limitations. ChatGPT is suitable for solving general problems. When a student comes across academic challenges, ChatGPT may…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, Error Patterns
Yun Huang; Christian Dieter Schunn; Julio Guerra; Peter L. Brusilovsky – ACM Transactions on Computing Education, 2024
Programming skills are increasingly important to the current digital economy, yet these skills have long been regarded as challenging to acquire. A central challenge in learning programming skills involves the simultaneous use of multiple component skills. This article investigates why students struggle with integrating component skills--a…
Descriptors: Programming, Computer Science Education, Error Patterns, Classification
Gloria Ashiya Katuka – ProQuest LLC, 2024
Dialogue act (DA) classification plays an important role in understanding, interpreting and modeling dialogue. Dialogue acts (DAs) represent the intended meaning of an utterance, which is associated with the illocutionary force (or the speaker's intention), such as greetings, questions, requests, statements, and agreements. In natural language…
Descriptors: Dialogs (Language), Classification, Intention, Natural Language Processing
Sharp, Jason H.; Mitchell, Alanah; Lang, Guido – Journal of Information Systems Education, 2020
In this paper, we analyze and categorize research related to Agile teaching and learning in Information Systems education using an existing conceptual framework. To this end, a systematic literature review beginning with 642 papers led to the identification of 30 relevant papers written in English and published through 2018 in academic IS outlets.…
Descriptors: Teaching Methods, Information Systems, Information Science Education, Computer Software
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
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
Pimpuang, Kowit; Yuttapongtada, Methawee – LEARN Journal: Language Education and Acquisition Research Network, 2023
The objectives of this research article were to study the relations of Sanskrit to English, to investigate English words identified as of Sanskrit origin which are loanwords in the Thai language and to explore the effects of using WordWall gamification for English words of Sanskrit origin in Thai learning. The samples consisted of seven master's…
Descriptors: Classical Languages, Linguistic Borrowing, Thai, Intervention
Zhou, Yiqiu; Kang, Jina – International Educational Data Mining Society, 2022
The complex and dynamic nature of collaboration makes it challenging to find indicators of productive learning and quality collaboration. This exploratory study developed a collaboration metric to capture temporal patterns of joint attention (JA) based on log files generated as students interacted with an immersive astronomy simulation using…
Descriptors: Astronomy, Problem Solving, Science Instruction, Cooperative Learning
Nicula, Bogdan; Dascalu, Mihai; Newton, Natalie N.; Orcutt, Ellen; McNamara, Danielle S. – Grantee Submission, 2021
Learning to paraphrase supports both writing ability and reading comprehension, particularly for less skilled learners. As such, educational tools that integrate automated evaluations of paraphrases can be used to provide timely feedback to enhance learner paraphrasing skills more efficiently and effectively. Paraphrase identification is a popular…
Descriptors: Computational Linguistics, Feedback (Response), Classification, Learning Processes
El Aissaoui, Ouafae; El Alami El Madani, Yasser; Oughdir, Lahcen; El Allioui, Youssouf – Education and Information Technologies, 2019
Adaptive E-learning platforms provide personalized learning process relying mainly on learning styles. The traditional approach to find learning styles depends on asking learners to self-evaluate their own attitudes and behaviors through surveys and questionnaires. This approach presents several weaknesses including the lack of self-awareness of…
Descriptors: Classification, Cognitive Style, Models, Electronic Learning
Mao, Ye; Shi, Yang; Marwan, Samiha; Price, Thomas W.; Barnes, Tiffany; Chi, Min – International Educational Data Mining Society, 2021
As students learn how to program, both their programming code and their understanding of it evolves over time. In this work, we present a general data-driven approach, named "Temporal-ASTNN" for modeling student learning progression in open-ended programming domains. Temporal-ASTNN combines a novel neural network model based on abstract…
Descriptors: Programming, Computer Science Education, Learning Processes, Learning Analytics
Song, Yu; Lei, Shunwei; Hao, Tianyong; Lan, Zixin; Ding, Ying – Journal of Educational Computing Research, 2021
Due to benefits for teaching and learning, an increasing number of studies have focused on classroom dialogue and how to make it productive. Coding, in which the transcribed conversation is allocated to a set of features, is commonly employed to deal with the textual data arising from this dialogue. This is generally done manually and cannot…
Descriptors: Semantics, Classification, Classroom Communication, Dialogs (Language)
Lai, Song; Sun, Bo; Wu, Fati; Xiao, Rong – IEEE Transactions on Learning Technologies, 2020
Adaptive e-learning can be used to personalize learning environment for students to meet their individual demands. Individual differences depend on the students' personality traits. Numerous studies have indicated that understanding the role of personality in the learning process can facilitate learning. Hence, personality identification in…
Descriptors: Personality Traits, Electronic Learning, Individual Differences, Learning Processes
Steven Moore; John Stamper; Norman Bier; Mary Jean Blink – Grantee Submission, 2020
In this paper we show how we can utilize human-guided machine learning techniques coupled with a learning science practitioner interface (DataShop) to identify potential improvements to existing educational technology. Specifically, we provide an interface for the classification of underlying Knowledge Components (KCs) to better model student…
Descriptors: Learning Analytics, Educational Improvement, Classification, Learning Processes
Saito, Tomohiro; Watanobe, Yutaka – International Journal of Distance Education Technologies, 2020
Programming education has recently received increased attention due to growing demand for programming and information technology skills. However, a lack of teaching materials and human resources presents a major challenge to meeting this demand. One way to compensate for a shortage of trained teachers is to use machine learning techniques to…
Descriptors: Programming, Computer Science Education, Electronic Learning, Instructional Materials