SelectedWorks - Jui-Long Hung

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Selected Works of Jui-Long Hung

Professor, Department of Educational Technology

Dr. Jui-Long (Andy) Hung came to Boise State University as a Visiting Professor in 2007, and in 2008 joined the faculty in the Department of Educational Technology within the College of Education. He earned his Ed.D. in Instructional Technology from Texas Tech University in Lubbock, Texas, in 2007.

In addition to teaching graduate courses online, Dr. Hung's research interests include educational data mining and text mining, electronic performance support systems, automated tutoring agents, online software training, and educational gaming.

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About Jui-Long Hung

Dr. Jui-Long (Andy) Hung came to Boise State University as a Visiting Professor in 2007, and in 2008 joined the faculty in the Department of Educational Technology within the College of Education. He earned his Ed.D. in Instructional Technology from Texas Tech University in Lubbock, Texas, in 2007.

In addition to teaching graduate courses online, Dr. Hung's research interests include educational data mining and text mining, electronic performance support systems, automated tutoring agents, online software training, and educational gaming.

Articles (34)

S-KMN: Integrating Semantic Features Learning and Knowledge Mapping Network for Automatic Quiz Question Annotation (Jing Wang, Hao Li, Xu Du, et al.) Journal of King Saud University: Computer and Information Sciences (2023)

Quiz question annotation aims to assign the most relevant knowledge point to a question, which is a key technology to support intelligent education applications. However, the existing methods only extract the explicit semantic information that ...

Understanding College Students’ Cognitive Engagement in Online Collaborative Problem-Solving: A Multimodal Data Analysis (Hengtao Tang, Miao Dai, Xu Du, et al.) Distance Education (2023)

Laboratory experience is critical to foster college students’ collaborative problem-solving (CPS) abilities, but whether students stay cognitively engaged in CPS tasks during online laboratory sessions remains unknown. This study applied multimodal data analysis to examine ...

Impact of Big Data Analytics on Banking: A Case Study (Wu He, Jui-Long Hung and Lixin Liu) Journal of Enterprise Information Management (2023)

Purpose – The paper aims to help enterprises gain valuable knowledge about big data implementation in practice and improve their information management ability, as they accumulate experience, to reuse or adapt the proposed method to ...

Understand Group Interaction and Cognitive State in Online Collaborative Problem Solving: Leveraging Brain-to-Brain Synchrony Data (Xu Du, Lizhao Zhang, Jui-Long Hung, et al.) International Journal of Educational Technology in Higher Education (2022)

The purpose of this study aimed to analyze the process of online collaborative problem solving (CPS) via brain-to-brain synchrony (BS) at the problem-understanding and problem-solving stages. Aiming to obtain additional insights than traditional approaches (survey ...

Learning Anytime, Anywhere: A Spatio-Temporal Analysis for Online Learning (Xu Du, Mingyan Zhang, Brett E. Shelton, et al.) Interactive Learning Environments (2022)

The study proposes two new measures, time and location entropy, to depict students’ physical spatio-temporal contexts when engaged in an online course. As anytime, anywhere access has been touted as one of the most attractive ...

Using Multimodal Analytics to Systemically Investigate Online Collaborative Problem-Solving (Hengtao Tang, Miao Dai, Shuoqiu Yang, et al.) Distance Education (2022)

The purpose of this research was to apply multimodal learning analytics in order to systemically investigate college students’ attention states during their collaborative problem-solving (CPS) in online settings. Existing research on CPS relies on self-reported ...

A Systematic Meta-Review and Analysis of Learning Analytics Research (Xu Du, Juan Yang, Brett E. Shelton, et al.) Behaviour & Information Technology (2021)

As an emerging field of research, learning analytics (LA) offers practitioners and researchers information about educational data that is helpful for supporting decisions in management of teaching and learning. While often combined with educational data ...

Is Learning Anytime, Anywhere a Good Strategy for Success?: Identifying Successful Spatial-Temporal Patterns of On-the-Job and Full-Time Students (Xu Du, Juan Yang, Brett Shelton, et al.) Information Discovery and Delivery (2020)

Purpose – Online learning is well-known by its flexibility of learning anytime and anywhere. However, how behavioral patterns tied to learning anytime and anywhere influence learning outcomes are still unknown. Design/methodology/approach – This study proposed ...

Improving Predictive Power Through Deep Learning Analysis of K-12 Online Student Behaviors and Discussion Board Content (Jui-Long Hung, Kerry Rice, Jennifer Kepka, et al.) Information Discovery and Delivery (2020)

Purpose – For studies in educational data mining or learning Analytics, the prediction of student’s performance or early warning is one of the most popular research topics. However, research gaps indicate a paucity of research ...

Motivators of Attendance at Eco-Friendly Events (Yu (John) Ye, Ching-Hui (Joan) Su, Chin-Hsun (Ken) Tsai, et al.) Journal of Convention & Event Tourism (2020)

This study identifies the factors that attract U.S. residents to eco-friendly events. To achieve our research objective, we obtained data (N = 1,115) from a cross-national, web-based survey distributed to consumers 18 to 65 years ...

Big Data Analytics for Supply Chain Relationship in Banking (Jui-Long Hung, Wu He and Jiancheng Shen) Industrial Marketing Management (2020)

This paper reports how a commercial bank in Asia uses big data analytic as a tool to explore the internal B2B data to improve supply chain finance and the efficiency of marketing tactics and campaigns. ...

An Integrated Framework Based on Latent Variational Autoencoder for Providing Early Warning of At-Risk Students (Xu Du, Juan Yang and Jui-Long Hung) IEEE Access (2020)

The rapid development of learning technologies has enabled online learning paradigm to gain great popularity in both high education and K-12, which makes the prediction of student performance become one of the most popular research ...

Improving Predictive Modeling for At-Risk Student Identification: A Multistage Approach (Jui-Long Hung, Brett E. Shelton, Juan Yang, et al.) IEEE Transactions on Learning Technologies (2019)

Performance prediction is a leading topic in learning analytics research due to its potential to impact all tiers of education. This study proposes a novel predictive modeling method to address the research gaps in existing ...

Measuring and Comparing Service Quality Metrics Through Social Media Analytics: A Case Study (Wu He, Xin Tian, Andy Hung, et al.) Information Systems and E-Business Management (2018)

This paper proposes a framework of using social media analytics to help study service quality. A case study was conducted to collect and analyze a data set which included nearly half million tweets related to ...

Predicting Student Success by Modeling Student Interaction in Asynchronous Online Courses (Brett E. Shelton, Jui-Long Hung and Patrick R. Lowenthal) Distance Education (2017)

Early-warning intervention for students at risk of failing their online courses is increasingly important for higher education institutions. Students who show high levels of engagement appear less likely to be at risk of failing, and ...

Identifying At-Risk Students for Early Interventions—A Time-Series Clustering Approach (Jui-Long Hung, Morgan C. Wang, Shuyan Wang, et al.) IEEE Transactions on Emerging Topics in Computing (2017)

The purpose of this paper is to identify at-risk online students earlier, more often, and with greater accuracy using time-series clustering. The case study showed that the proposed approach could generate models with higher accuracy ...

Online Graduate Teacher Education: Establishing an EKG for Student Success Intervention (Brett E. Shelton, Jui-Long Hung and Sarah Baughman) Technology, Knowledge and Learning (2016)

Predicting which students enrolled in graduate online education are at-risk for failure is an arduous yet important task for teachers and administrators alike. This research reports on a statistical analysis technique using both static and ...

The Role of Trust Management in Reward-Based Crowdfunding (Haichao Zheng, Jui-long Hung, Zihao Qi, et al.) Online Information Review (2016)

Purpose – The purpose of this paper is to investigate the role of trust management on the fundraising performance in reward-based crowdfunding. Design/methodology/approach – A research model was constructed based on elaboration likelihood model (ELM) ...

The Validation of an Instrument for Evaluating the Effectiveness of Professional Development Program on Teaching Online (Jui-Long Hung and Dazhi Yang) Journal of Educational Technology Development and Exchange (2015)

Attending professional development (PD) on teaching online is becoming popular for teachers in today’s K-12 online education. Due to the unique characteristics of the online instructional environments, surveys become the most feasible approach to evaluate ...

A Hybrid Trust-Based Recommender System for Online Communities of Practice (Xiao-Lin Zheng, Chao-Chao Chen, Jui-Long Hung, et al.) IEEE Transactions on Learning Technologies (2015)

The needs for life-long learning and the rapid development of information technologies promote the development of various types of online Community of Practices (CoPs). In online CoPs, bounded rationality and metacognition are two major issues, ...

Data Mining in Online Professional Development Program Evaluation: An Exploratory Case Study (Kerry Rice and Jui-Long Hung) International Journal of Technology in Teaching & Learning (2015)

This case study explored the potential applications of data mining in the educational program evaluation of online professional development workshops for pre K-12 teachers. Multiple data mining analyses were implemented in combination with traditional evaluation ...

Trends of Educational Technology Research: More Than a Decade of International Research in Six SSCI-Indexed Refereed Journals (Yu-Chang Hsu, Jui-Long Hung and Yu-Hui Ching) Educational Technology Research and Development (2013)

This study applied text mining methods to examine the abstracts of 2,997 international research articles published between 2000 and 2010 by six journals included in the Social Science Citation Index in the field of Educational ...

An Educational Data Mining Model for Online Teaching and Learning (Jui-Long Hung, Kerry Rice and Anthony Saba) Journal of Educational Technology Development and Exchange (2012)

This study contains two major parts. First, this study proposed a generic model for Educational Data Ming (EDM) studies by reviewing EDM literature and the existing data mining model. Second, the procedures of the EDM ...

Integrating Data Mining in Program Evaluation of K-12 Online Education (Jui-long Hung, Yu-Chang Hsu and Kerry Rice) Journal of Educational Technology & Society (2012)

This study investigated an innovative approach of program evaluation through analyses of student learning logs, demographic data, and end-of-course evaluation surveys in an online K–12 supplemental program. The results support the development of a program ...

Examining Mobile Learning Trends 2003–2008: A Categorical Meta-Trend Analysis Using Text Mining Techniques (Jui-long Hung and Ke Zhang) Journal of Computing in Higher Education (2012)

This study investigated the longitudinal trends of academic articles in Mobile Learning (ML) using text mining techniques. One hundred and nineteen (119) refereed journal articles and proceedings papers from the SCI/SSCI database were retrieved and ...