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Tianyuan Yang; Baofeng Ren; Chenghao Gu; Boxuan Ma; Shin 'ichi Konomi – International Association for Development of the Information Society, 2024
As education increasingly shifts towards a technology-driven model, artificial intelligence systems like ChatGPT are gaining recognition for their potential to enhance educational support. In university education and MOOC environments, students often select courses that align with their specific needs. During this process, access to information…
Descriptors: Concept Formation, Artificial Intelligence, Computer Uses in Education, MOOCs
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Wan, Qian; Crossley, Scott; Banawan, Michelle; Balyan, Renu; Tian, Yu; McNamara, Danielle; Allen, Laura – International Educational Data Mining Society, 2021
The current study explores the ability to predict argumentative claims in structurally-annotated student essays to gain insights into the role of argumentation structure in the quality of persuasive writing. Our annotation scheme specified six types of argumentative components based on the well-established Toulmin's model of argumentation. We…
Descriptors: Essays, Persuasive Discourse, Automation, Identification
Saira Anwar; Ahmed Ashraf Butt; Muhsin Menekse – Grantee Submission, 2023
This study explored the effectiveness of scaffolding in students' reflection writing process. We compared two sections of an introductory computer programming course (N=188). In Section 1, students did not receive any scaffolding while generating reflections, whereas in Section 2, students were scaffolded during the reflection writing process.…
Descriptors: Scaffolding (Teaching Technique), Writing Instruction, Writing Processes, Writing (Composition)
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Xiao, Yunkai; Zingle, Gabriel; Jia, Qinjin; Akbar, Shoaib; Song, Yang; Dong, Muyao; Qi, Li; Gehringer, Edward – International Educational Data Mining Society, 2020
Peer assessment adds value when students provide "helpful" feedback to their peers. But, this begs the question of how we determine "helpfulness." One important aspect is whether the review detects problems in the submitted work. To recognize problem detection, researchers have employed NLP and machine-learning text…
Descriptors: Peer Evaluation, Problems, Identification, Natural Language Processing
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Jia, Qinjin; Cui, Jialin; Xiao, Yunkai; Liu, Chengyuan; Rashid, Parvez; Gehringer, Edward – International Educational Data Mining Society, 2021
Peer assessment has been widely applied across diverse academic fields over the last few decades, and has demonstrated its effectiveness. However, the advantages of peer assessment can only be achieved with high-quality peer reviews. Previous studies have found that high-quality review comments usually comprise several features (e.g., contain…
Descriptors: Peer Evaluation, Models, Artificial Intelligence, Evaluation Methods
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Pugh, Samuel L.; Subburaj, Shree Krishna; Rao, Arjun Ramesh; Stewart, Angela E. B.; Andrews-Todd, Jessica; D'Mello, Sidney K. – International Educational Data Mining Society, 2021
We investigated the feasibility of using automatic speech recognition (ASR) and natural language processing (NLP) to classify collaborative problem solving (CPS) skills from recorded speech in noisy environments. We analyzed data from 44 dyads of middle and high school students who used videoconferencing to collaboratively solve physics and math…
Descriptors: Problem Solving, Cooperation, Middle School Students, High School Students
Snyder, Robin M. – Association Supporting Computer Users in Education, 2015
The field of topic modeling has become increasingly important over the past few years. Topic modeling is an unsupervised machine learning way to organize text (or image or DNA, etc.) information such that related pieces of text can be identified. This paper/session will present/discuss the current state of topic modeling, why it is important, and…
Descriptors: Natural Language Processing, Artificial Intelligence, Man Machine Systems, Computational Linguistics
Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S. – Grantee Submission, 2015
This study builds upon previous work aimed at developing a student model of reading comprehension ability within the intelligent tutoring system, iSTART. Currently, the system evaluates students' self-explanation performance using a local, sentence-level algorithm and does not adapt content based on reading ability. The current study leverages…
Descriptors: Reading Comprehension, Reading Skills, Natural Language Processing, Intelligent Tutoring Systems
Liu, Hong P.; Klein, Jerry E. – International Association for Development of the Information Society, 2013
With the increasing complexity of technology and large quantities of data in our digital age, learning and training has become a major cost of employers. Employee competence depends more and more on how quickly one can acquire new knowledge and solve problems to meet pressing deadlines. This paper presents a practical method to use REU (Research…
Descriptors: Undergraduate Students, Student Research, Research Projects, Student Projects