Jui-Long Hung

Boise State University | BSU · Department of Educational Technology

Learner engagement in online courses is impacted by a wide variety of factors. The purpose of this study was to understand to what extent course community support and personal community support influence learner engagement. Students who had recently completed an online course in a small art and design school were surveyed on their level of engageme...

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 reveals the literal meaning of a question, and ignore the implicit knowledge information that highlights t...

Purpose Student engagement is a key factor that connects with student achievement and retention. This paper aims to identify individuals' engagement automatically in the classroom with multimodal data for supporting educational research. Design/methodology/approach The video and electroencephalogram data of 36 undergraduates were collected to repr...

Blended learning has been widely integrated in college-level computer science education. Despite evidence about benefits of blended learning, students’ in-class activities remain underexplored. To afford effective blended learning experience, supporting students in both modalities is essential. This study thus took an initial step to fill the gap b...

This study aims to track college students’ on-task rate during the teaching process and to analyze the influence of instructional strategies on on-task rate through the aspects of observable and internal engagement indicators. Thirty-six undergraduate students at a higher education institution in China participated in the study. Students’ behaviors...

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 achieve a sustainable competitive advantage. Design/methodology/approach Guided by the theory of technological frames...

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 and observation), BS refers to the synchronization of brain activity between two or m...

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 data, which limits the validity of the findings. This study looked at data in a systemic...

Distance education programs have become the preferred option for most higher education institutions to continue teaching during the COVID-19 pandemic, but the effectiveness of some online courses, especially those engineering courses with experimentation activities, remains disputed. The main challenge is fostering collaborative problem solving ski...

In online learning, students’ learning behavior might change as the course progresses. How students adjust learning behaviors aligned with course requirements reflects their self-regulated learning strategies. Analyzing students’ learning patterns can help instructors understand how the course design or activities shape students’ learning behaviors...

Purpose Critical thinking is considered important in psychological science because it enables students to make effective decisions and optimizes their performance. Aiming at the challenges and issues of understanding the student's critical thinking, the objective of this study is to analyze online discussion data through an advanced multi-feature f...

Purpose This study aims to propose a learning pattern analysis method which can improve a predictive model’s performance, as well as discover hidden insights into micro-level learning pattern. Analyzing student’s learning patterns can help instructors understand how their course design or activities shape learning behaviors; depict students’ belief...

Purpose The purpose of this study is to conduct a systematic review to understand state-of-art research related to learning preferences from the aspects of impacts, influential factors and evaluation methods. Design/methodology/approach This paper uses the systematic synthesis method to provide state-of-the-art knowledge on learning preference res...

As a student modeling technique, knowledge tracing is widely used by various intelligent tutoring systems to infer and trace the individual’s knowledge state during the learning process. In recent years, various models were proposed to get accurate and easy-to-interpret results. To make sense of the wide Knowledge tracing (KT) modeling landscape, t...

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 of age living in the continental United States. The questionnaire was comprised of five multi-item summated rating scale...

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 using machine learning and deep learning (DL) models in predictive analytics that include both behaviors and text analysis....

Purpose Educational data mining (EDM) and learning analytics, which are highly related subjects but have different definitions and focuses, have enabled instructors to obtain a holistic view of student progress and trigger corresponding decision-making. Furthermore, the automation part of EDM is closer to the concept of artificial intelligence. Due...

This study proposes two innovative approaches, the 1-channel learning image recognition (1-CLIR) and the 3-channel learning image recognition (3-CLIR) to convert student's course involvements into images for early warning predictive analysis. Multiple experiments with 5,235 students and 576 absolute/1728 relative input variables were conducted to v...

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 topics in education. However, the traditional prediction algorithms are originally designed for balanced dataset, whil...

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 concepts of time and location entropy to depict students’ spatial-temporal patterns. A total...

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. A case study was conducted by analyzing two types of supply chain relationships: (1) supply chain relationships in the credit reports; (2) e-wiring...

Nowadays, it is no longer appropriate to evaluate students’ performance just only using the final exam scores, the learning procedure should be taken into account as the compensation. Online discussion is widely employed and is one important component in blend learning. Combining participation and the depth of thinking, we propose a model to evalua...

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 mining (EDM), crucial distinctions exist for LA that mandate a separate review. This study aims...

Learning analytics (LA) and educational data mining (EDM) are highly related subjects that overlap in de fi nition and scope. Although both communities of researchers within LA and EDM have similarities where learning science and analytic techniques intersect, there are some signi fi cant differences between them in terms of origins, techniques, fi...

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 performance prediction research. The gaps addressed include: the lack of existing research focus on performance prediction rat...

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 features of online learning, the question remains as to the success of students when engaging in online courses through disp...

Research in learning analytics is proliferating as scholars continue to find better and more engaging ways to consider how data can help inform evidence-based decisions for learning and learning environments. With well over a thousand articles published in journals and conferences with respect to learning analytics, only a handful or articles exist...

This study proposes an analytic approach which combines two predictive models (the predictive model of successful students and the predictive model of at-risk students) to enhance prediction performance for use under the constraints of limited data collection. A case study was conducted to examine the effects of the model combination approach. Eigh...

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 two of the largest supermarkets in the United States: Walmart and Kmart. The results illustrate how businesses can leverage external open dat...

The purpose of the proposed project is to develop and validate a virtual Hebb-Williams (vHW) maze task for use as a low-cost, time-efficient, and easy-to-use assessment for the early detection of children at risk for reading impairment. The vHW maze offers the potential to serve as a reliable, non-language based predictor of reading difficulty, whi...

In the traditional e-learning environment lack of immediate learning assistance. This online adaptive learning and recommendation platform (ALR) provide tracking tool for instructors to “observe” or “monitor” individual students’ learning activities. Students can learn through the ALR platform using the learning path to get the immediate assistance...

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 how engaged a student is in their online experience can be characterized as factors contributing to their social pre...

IntroductionSince 2015 is the year of FinTech in Taiwan, it is worth investigating the challenges that emerged when banks were encouraged to invest in FinTech companies for collaboration. This study aims to identify the strategic considerations in the process of searching for FinTech investment targets. Case descriptionThis study used a case study...

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) and literatures with five hypotheses developed. Data were collected from www.demohour.com - the fi...

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, especially when learners face information overload and there is no knowledge authority within the learnin...

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 dynamic variables to determine which students are at-risk and when an intervention could be most helpful durin...

Purpose – The purpose of this paper is investigating the value of service guarantee (SG) program in Service e-Commerce (SeC) which is one resolution to promote service transactions. SeC is emerging as a booming form of e-commerce where various services are contracted, managed, sold and even delivered via the Internet. However, the uncertainty of se...

the purpose of this study 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 and feasibility than traditional frequency aggregation approaches. The best performing model can start to capture at...

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 instruments and student outcomes to determine learner engagement and more clearly under...

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 Technology (EDTECH). A total of 19 clusters of research areas were identified, and these clusters were further analyzed in...

Purpose In December 2011, the National Computer Network Emergency Response Technical Team/Coordination Center of China reported the most serious user data leak in history which involved 26 databases with 278 million user accounts and passwords. After acquiring the user data from this massive information leak, this study has two major research purpo...

Service e-Commerce (SeC) is emerging as a booming form of e-commerce where various services are contracted, managed, sold, and even delivered via the Internet. However, the uncertainty of service quality due to information asymmetry has been a major challenge to the development of SeC. Some SeC platforms tried to promote service business by lowerin...

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 model are demonstrated with a case study approach. The case study results showed patterns and relationships discovered from the EDM...

Between December 21 and 25, 2011, hackers released more than 100 million users' account information, from China's most popular websites, including usernames, passwords, and emails. As user passwords were not encrypted, the online security crisis has caused prevailing panic among many Internet users in China. On the other hand, this online security...

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 evaluation model for decision making on teaching and learning at the K–12 level. A case study w...

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 model are demonstrated with a case study approach. The case study results showed patterns and relationships discovered from the EDM...

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 analyzed. The taxonomies of ML publications were grouped into twelve clusters (topics) and four domai...

This study investigated the longitudinal trends of e-learning research using text mining techniques. Six hundred and eighty-nine (689) refereed journal articles and proceedings were retrieved from the Science Citation Index/Social Science Citation Index database in the period from 2000 to 2008. All e-learning publications were grouped into two doma...

This case study investigated undergraduate students’ first experience in online collaborative learning in a project‐based learning (PBL) environment in Taiwan. Data were collected through interviews of 48 students, instructor’s field notes, researchers’ online observations, students’ online discourse, and group artifacts. The findings revealed inte...

The student learning process is important in online learning environments. If instructors can "observe" online learning behaviors, they can provide adaptive feedback, adjust instructional strategies, and assist students in establishing patterns of successful learning activities. This study used data mining techniques to examine and compare learning...

This study was conducted with data mining (DM) techniques to analyze various patterns of online learning behaviors, and to make predictions on learning outcomes. Statistical models and machine learning DM techniques were conducted to analyze 17,934 server logs to investigate 98 undergraduate students' learning behaviors in an online business course...

As Taiwan's full-scale e-learning initiatives moved to the seventh year in 2009, the current status and challenges of e-learning development there are yet to be fully understood. Further extending Zhang and Hung's (2006) investigation on e-learning in all universities and colleges in Taiwan, this study investigated the after-school programs (ASPs)...

It has been three years since Taiwan started the comprehensive e-learning initiatives in 2002. What is the current status of Taiwan’s e-learning in higher education? What has been shaping and guiding the e-learning practices there? What are the problems in its e-learning policies and implementations? What can policy makers and higher education syst...

Following cognitive load theory, we used a computer-based software training paradigm to determining the optimal number of steps or information chunks to present before practice opportunities. Results demonstrating that the size of information chunks presented and the type of practice used individually influenced participants' ability to effectively...