Jui-long Hung

Loose Password Security in Chinese Cyber World Left the Front Door Wide Open to Hackers—An Analytic View

Cheng Yang et al. — Wed, 03 Oct 2012 14:20:21 PDT

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 disaster also provides researchers priceless data with which to study users' password patterns, especially when comparing those patterns across various relevant websites. Lessons thusly learned can help Chinese online service providers improve their service security in the future. This paper reports the findings from the exploratory study of the datasets from the affected websites with more than 60 million records, including (1) users might choose less secure passwords for their convenience and ease of memorization, though their primary concern is online security; (2) for the same reasons, password reuse is common, as users tend to use the same passwords for multiple online accounts; and (3) passwords usually contain common words, or personal information, such as birthdays and family member names.

Integrating Data Mining in Program Evaluation of K-12 Online Education

Jui-long Hung et al. — Tue, 11 Sep 2012 15:50:20 PDT

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 was conducted with a total of 7,539 students (whose activities resulted in 23,854,527 learning logs in 883 courses). Clustering analysis was applied to reveal students’ shared characteristics, and decision tree analysis was applied to predict student performance and satisfaction levels toward course and instructor. This study demonstrated how data mining can be incorporated into program evaluation in order to generate in-depth information for decision making. In addition, it explored potential EDM applications at the K- 12 level that have already been broadly adopted in higher education institutions.

Examining Mobile Learning Trends 2003–2008: A Categorical Meta-Trend Analysis Using Text Mining Techniques

Jui-long Hung et al. — Fri, 16 Sep 2011 09:32:57 PDT

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 domains, based on abstract analysis using text mining. Results include basic bibliometric statistics, trends in frequency of each topic over time, predominance in each topic by country, and preferences for each topic by journal. Key findings include the following: (a) ML articles increased from 8 in 2003 to 36 in 2008; (b) the most popular domain in current ML is Effectiveness, Evaluation, and Personalized Systems; (c) Taiwan is most prolific in five of the twelve ML clusters; (d) ML research is at the Early Adopters stage; and (e) studies in strategies and framework will likely produce a bigger share of publication in the field of ML.

Trends of E-Learning Research from 2000 to 2008: Use of Text Mining and Bibliometrics

Jui-long Hung — Fri, 16 Sep 2011 09:32:56 PDT

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 domains with four groups/15 clusters based on abstract analysis. Three additional variables: subject areas, prolific countries and prolific journals were applied to data analysis and data interpretation. Conclusions include that e-learning research is at the early majority stage and foci have shifted from issues of the effectiveness of e-learning to teaching and learning practices. Educational studies and projects and e-learning application in medical education and training are growing fields with the highest potential for future research. Approaches to e-learning differ between leading countries and early adopter countries, and government policies play an important role in shaping the results.

Designing Electronic Performance Support System to Facilitate Computer-Based Software Training

J.L. Hung et al. — Wed, 18 May 2011 15:56:55 PDT

An electronic performance support system (EPSS) is a computer-based environment that facilitates skill and knowledge acquisition within a particular domain. The authors’ on-going research will investigate the potential utility of EPSS tools in software training field. This paper discusses the necessity of embedded EPSS in the software training. A computer-based software training program with embedded EPSS for Microsoft Excel is developed for the study. This paper also describes the design and implementation process of the system. The effectiveness of the EPSS prototype tools will be investigated through quantitative methods. The results will provide theoretical and practical implications for improvement of computer-based software training.

The Effects of Segment Size and Practice During Computer-Based Software Training

J.L. Hung et al. — Wed, 18 May 2011 15:52:19 PDT

Developing a Customized Data Mining Model for Online Professional Development Evaluation

Kerry Rice et al. — Wed, 18 May 2011 15:46:21 PDT

E-Learning in Supplemental Educational Systems in Taiwan: Present Status and Future Challenges

Ke Zhang et al. — Wed, 18 May 2011 15:13:32 PDT

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) in Taiwan. ASPs are an interesting social phenomenon in Asian culture. As influential supplemental educational systems (SES), they are popularly available at all educational levels (K-20) as well as in those highly in-demand training or continuing education areas. This article reviews the current status and trends of the SES in Taiwan while also analyzing related guiding policies, identifying challenges in e-learning implementation in these systems, and concluding with suggestions to address these issues. The findings are of particular value not only for policy makers in Taiwan and other countries or regions with similar problems, but also for e-learning vendors and developers aiming to better understand as well as extend the e-learning market within Taiwan and other areas with similar cultures.

Examining Online Learning Patterns with Data Mining Techniques in Peer-Moderated and Teacher-Moderated Courses

Jui-long Hung et al. — Wed, 18 May 2011 12:57:49 PDT

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 patterns between peer-moderated and teacher-moderated groups from a recently completed experimental study (Zhang, Peng, & Hung, 2009). The online behaviors of the students from the Zhang et al. study were analyzed to determine why teacher-moderated groups performed significantly better than peer-moderated groups. Three data mining techniques—clustering analysis, association rule analysis, and decision tree analysis—were used for data analysis. The results showed that most students in the peer-moderated condition had low participation levels and relied on student-content interaction only. On the other hand, teacher presence promoted student interaction with multiple sources (content, student, and teacher). The findings demonstrate the potential of data mining techniques to support teaching and learning.

E-Learning in Taiwan's Higher Education: Policies, Practices, and Problems

Ke Zhang et al. — Tue, 17 May 2011 15:43:59 PDT

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 systems elsewhere learn from Taiwan’s experiences? With critical analyses on related policies and a thorough investigation on e-learning in all of the 147 four-year universities in Taiwan, this study investigated these questions, identified fundamental problems in Taiwan’s e-learning, and generated suggestions to address these problems. With 1.3 billion Chinese speakers worldwide and estimated 30 million people learning Chinese in non-Chinese speaking countries, this paper is of particular value not only for policy makers and the higher education system in Taiwan and elsewhere, but also for e-learning venders and developers who would like to extend e-learning business to the broader Chinese-speaking market.

Taiwan Higher Education’s E-Learning: Status and Critical Reflections

Ke Zhang et al. — Tue, 17 May 2011 15:38:56 PDT

Computer-Based Instruction and Cognitive Load

Jui-long Hung et al. — Thu, 02 Sep 2010 15:30:23 PDT

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 learn via computer-based instruction. These findings contribute to the literature by showing the importance of practice and optimal segment sizes for learning via a computer.

Revealing Online Learning Behaviors and Activity Patterns and Making Predictions with Data Mining Techniques in Online Teaching

Jui-long Hung et al. — Tue, 31 Aug 2010 15:50:04 PDT

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 in Taiwan. The study scientifically identified students’ behavioral patterns and preferences in the online learning processes, differentiated active and passive learners, and found important parameters for performance prediction. The results also demonstrated how data mining techniques might be utilized to help improve online teaching and learning with suggestions for online instructors, instructional designers and courseware developers.

Mining Longitudinal E-Learning Research: Trends and Patterns

Jui-long Hung — Fri, 20 Aug 2010 09:43:51 PDT

Mining Topic Taxonomies of the Distance Education Literature With Text-Mining Techniques

Jui-long Hung et al. — Fri, 20 Aug 2010 09:34:30 PDT

This study investigated the longitudinal trends of distance education research through text mining. Selected text mining techniques were used to extract implicit, hidden knowledge from the open source distance education literature available from Web of Knowledge database. The taxonomies of distance education articles were grouped into clusters based on abstract analysis with text mining techniques. The results illustrate the trends of research across time in the field of distance education, generate article biblio-metrix, and show the overall research themes from 1981 to 2008 in distance education research.

ERP Research from 2003 to 2009: A Study of Meta-Trend Analysis Using Text Mining Techniques

Jui-long Hung — Fri, 20 Aug 2010 09:30:09 PDT

Online Collaborative Learning in a Project-based Learning Environment in Taiwan: A Case Study on Undergraduate Students’ Perspectives

Ke Zhang et al. — Mon, 17 May 2010 15:12:26 PDT

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 interesting phenomena as results of cultural influences as well as educational system impacts. Students experienced first handed various learning benefits of PBL in the intensive six-week period, yet voiced serious concerns about the changed role of the instructor, as well as strong reservations on peer collaboration as a result of the competitive tradition in education. Obviously, online collaborative learning and PBL critically challenged some culturally-rooted traditions in Taiwan. The study generates practical insights into the applications of online collaborative learning and PBL in Taiwan’s higher education as well as implications for cross-cultural implementation of online learning.