Personalized e-learning system using Item Response Theory
TL;DR: This study proposes a personalized e-learning system based on Item Response Theory (PEL-IRT) which considers both course material difficulty and learner ability to provide individual learning paths for learners and shows that applying Item Response theory to Web-based learning can achieve personalized learning and help learners to learn more effectively and efficiently.
Abstract: Personalized service is important on the Internet, especially in Web-based learning. Generally, most personalized systems consider learner preferences, interests, and browsing behaviors in providing personalized services. However, learner ability usually is neglected as an important factor in implementing personalization mechanisms. Besides, too many hyperlink structures in Web-based learning systems place a large information burden on learners. Consequently, in Web-based learning, disorientation (losing in hyperspace), cognitive overload, lack of an adaptive mechanism, and information overload are the main research issues. This study proposes a personalized e-learning system based on Item Response Theory (PEL-IRT) which considers both course material difficulty and learner ability to provide individual learning paths for learners. The item characteristic function proposed by Rasch with a single difficulty parameter is used to model the course materials. To obtain more precise estimation of learner ability, the maximum likelihood estimation (MLE) is applied to estimate learner ability based on explicit learner feedback. Moreover, to determine an appropriate level of difficulty parameter for the course materials, this study also proposes a collaborative voting approach for adjusting course material difficulty. Experiment results show that applying Item Response Theory (IRT) to Web-based learning can achieve personalized learning and help learners to learn more effectively and efficiently.
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TL;DR: It is demonstrated that instructors have very positive perceptions toward using e- learning as a teaching assisted tool, and guidelines for developing e-learning environments are proposed.
Abstract: The trend of using e-learning as a learning and/or teaching tool is now rapidly expanding into education. Although e-learning environments are popular, there is minimal research on instructors' and learners' attitudes toward these kinds of learning environments. The purpose of this study is to explore instructors' and learners' attitudes toward e-learning usage. Accordingly, 30 instructors and 168 college students are asked to answer two different questionnaires for investigating their perceptions. After statistical analysis, the results demonstrate that instructors have very positive perceptions toward using e-learning as a teaching assisted tool. Furthermore, behavioral intention to use e-learning is influenced by perceived usefulness and self-efficacy. Regarding to learners' attitudes, self-paced, teacher-led, and multimedia instruction are major factors to affect learners' attitudes toward e-learning as an effective learning tool. Based on the findings, this research proposes guidelines for developing e-learning environments.
719 citations
TL;DR: This study investigates critical factors on e-learning adoption in South Korea and proposes a research model which consists of four independent variables (instructor characteristics, teaching materials, design of learning contents, and playfulness), two belief variables (perceived usefulness and perceived ease of use), and one dependent variable (intention to use e- learning).
Abstract: One of the most significant changes in the field of education in this information age is the paradigm shift from teacher-centered to learner-centered education. Along with this paradigm shift, understanding of students' e-learning adoption behavior among various countries is urgently needed. South Korea's dense student population and high educational standards made investment in e-learning very cost-effective. However, despite the fact that South Korea is one of the fastest growing countries in e-learning, not much of the research results have been known to the globalized world. By investigating critical factors on e-learning adoption in South Korea, our study attempts to fill a gap in the individual country-level e-learning research. Based on the extensive literature review on flow theory, service quality, and the Technology Acceptance Model, our study proposes a research model which consists of four independent variables (instructor characteristics, teaching materials, design of learning contents, and playfulness), two belief variables (perceived usefulness and perceived ease of use), and one dependent variable (intention to use e-learning). Results of regression analyses are presented. Managerial implications of the findings and future research directions are also discussed.
559 citations
Cites background from "Personalized e-learning system usin..."
...Playfulness is a complex variable which includes individual’s pleasure, psychological stimulation, and interests (Csikszentmihalyi, 1990). Moon and Kim (2001) view playfulness as a situational characteristic of the interaction between an individual and the situation. Three dimensions of perceived playfulness proposed by Moon and Kim (2001) are the extent to which the individual: (1) perceives that his or her attention is focused on the interaction with the web-based system; (b) is curious during the interaction; and (3) finds the interaction intrinsically enjoyable or interesting....
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...Playfulness is a complex variable which includes individual’s pleasure, psychological stimulation, and interests (Csikszentmihalyi, 1990). Moon and Kim (2001) view playfulness as a situational characteristic of the interaction between an individual and the situation....
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TL;DR: In this article, the authors present a context framework that identifies relevant context dimensions for TEL applications and present an analysis of existing TEL recommender systems along these dimensions, based on their survey results, they outline topics on which further research is needed.
Abstract: Recommender systems have been researched extensively by the Technology Enhanced Learning (TEL) community during the last decade. By identifying suitable resources from a potentially overwhelming variety of choices, such systems offer a promising approach to facilitate both learning and teaching tasks. As learning is taking place in extremely diverse and rich environments, the incorporation of contextual information about the user in the recommendation process has attracted major interest. Such contextualization is researched as a paradigm for building intelligent systems that can better predict and anticipate the needs of users, and act more efficiently in response to their behavior. In this paper, we try to assess the degree to which current work in TEL recommender systems has achieved this, as well as outline areas in which further work is needed. First, we present a context framework that identifies relevant context dimensions for TEL applications. Then, we present an analysis of existing TEL recommender systems along these dimensions. Finally, based on our survey results, we outline topics on which further research is needed.
527 citations
TL;DR: In this paper, a meta-analysis was conducted on research that compared the outcomes from students learning from Intelligent Tutoring Systems (ITS) to those learning from non-ITS learning environments.
Abstract: Intelligent Tutoring Systems (ITS) are computer programs that model learners’ psychological states to provide individualized instruction. They have been developed for diverse subject areas (e.g., algebra, medicine, law, reading) to help learners acquire domain-specific, cognitive and metacognitive knowledge. A meta-analysis was conducted on research that compared the outcomes from students learning from ITS to those learning from non-ITS learning environments. The meta-analysis examined how effect sizes varied with type of ITS, type of comparison treatment received by learners, type of learning outcome, whether knowledge to be learned was procedural or declarative, and other factors. After a search of major bibliographic databases, 107 effect sizes involving 14,321 participants were extracted and analyzed. The use of ITS was associated with greater achievement in comparison with teacher-led, large-group instruction (g .42), non-ITS computer-based instruction (g .57), and textbooks or workbooks (g .35). There was no significant difference between learning from ITS and learning from individualized human tutoring (g –.11) or small-group instruction (g .05). Significant, positive mean effect sizes were found regardless of whether the ITS was used as the principal means of instruction, a supplement to teacher-led instruction, an integral component of teacher-led instruction, or an aid to homework. Significant, positive effect sizes were found at all levels of education, in almost all subject domains evaluated, and whether or not the ITS provided feedback or modeled student misconceptions. The claim that ITS are relatively effective tools for learning is consistent with our analysis of potential publication bias.
393 citations
Cites methods from "Personalized e-learning system usin..."
...In this early ITS, like many that have been designed since, the student model was an overlay or subset of the domain model....
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...However, we do categorize as an ITS, and have included in our meta-analysis, an adaptive instructional system that uses item response theory to model student knowledge on multiple dimensions (C. M. Chen, Lee, & Chen, 2005)....
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TL;DR: Experimental results indicated that applying the proposed genetic-based personalized e-learning system for web-based learning is superior to the freely browsing learning mode because of high quality and concise learning path for individual learners.
Abstract: Personalized curriculum sequencing is an important research issue for web-based learning systems because no fixed learning paths will be appropriate for all learners. Therefore, many researchers focused on developing e-learning systems with personalized learning mechanisms to assist on-line web-based learning and adaptively provide learning paths in order to promote the learning performance of individual learners. However, most personalized e-learning systems usually neglect to consider if learner ability and the difficulty level of the recommended courseware are matched to each other while performing personalized learning services. Moreover, the problem of concept continuity of learning paths also needs to be considered while implementing personalized curriculum sequencing because smooth learning paths enhance the linked strength between learning concepts. Generally, inappropriate courseware leads to learner cognitive overload or disorientation during learning processes, thus reducing learning performance. Therefore, compared to the freely browsing learning mode without any personalized learning path guidance used in most web-based learning systems, this paper assesses whether the proposed genetic-based personalized e-learning system, which can generate appropriate learning paths according to the incorrect testing responses of an individual learner in a pre-test, provides benefits in terms of learning performance promotion while learning. Based on the results of pre-test, the proposed genetic-based personalized e-learning system can conduct personalized curriculum sequencing through simultaneously considering courseware difficulty level and the concept continuity of learning paths to support web-based learning. Experimental results indicated that applying the proposed genetic-based personalized e-learning system for web-based learning is superior to the freely browsing learning mode because of high quality and concise learning path for individual learners.
353 citations
Cites background from "Personalized e-learning system usin..."
...Based on the results of pre-test, the proposed genetic-based personalized e-learning system can conduct personalized curriculum sequencing through simultaneously considering courseware difficulty level and the concept continuity of learning paths to support web-based learning....
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...…personalized/adaptive guidance mechanisms, such as adaptive presentation, adaptive navigation support, curriculum sequencing, and intelligent analysis of student’s solutions, have been proposed (Chen et al., 2005; Papanikolaou & Grigoriadou, 2002; Tang & Mccalla, 2003; Weber & Specht, 1997)....
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...On the other hand, some researchers emphasized that personalization should consider levels of learner knowledge, especially in relation to learning (Chen et al., 2005; Chen, Liu, & Chang, 2006; Papanikolaou & Grigoriadou, 2002)....
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References
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Proceedings Article•
11 Nov 1999
TL;DR: This paper describes PageRank, a mathod for rating Web pages objectively and mechanically, effectively measuring the human interest and attention devoted to them, and shows how to efficiently compute PageRank for large numbers of pages.
Abstract: The importance of a Web page is an inherently subjective matter, which depends on the readers interests, knowledge and attitudes. But there is still much that can be said objectively about the relative importance of Web pages. This paper describes PageRank, a mathod for rating Web pages objectively and mechanically, effectively measuring the human interest and attention devoted to them. We compare PageRank to an idealized random Web surfer. We show how to efficiently compute PageRank for large numbers of pages. And, we show how to apply PageRank to search and to user navigation.
14,400 citations
Additional excerpts
...To help Internet users to search more efficiently, many powerful search tools (Brin & Page, 1998; Chidlovskii & Glance, 2000; Direct Hit, 2000; Kleinberg, 1998) have been proposed, such as the Google search engine (Google), or the Citeseer website (NEC Research Institute ResearchIndex)....
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Book•
01 Jan 1932
TL;DR: The instrument to be described here is not, however, indirect in the usual sense of the word; it does not seek responses to items apparently unrelated to the attitudes investigated, and seeks to measure prejudice in a manner less direct than is true of the usual prejudice scale.
Abstract: THIS paper describes a technique which has been developed for the measurement of race prejudice. This technique differs from most prejudice inventories in that it avoids the following assumptions: (a) that the individual can say, to his own or the investigator's satisfaction, "This is how prejudiced I am," and (b) that, to the extent that the individual can accurately assess his degree of antipathy, he will report honestly the findings of such introspection. Most sociologists would perhaps agree that race attitudes rarely reside on a completely articulate level. Even where the individual holds to intellectual or ideological convictions which would seem to leave no room for out-group antipathies, such do persevere. Thus, we may expect the number of Americans who honestly think themselves "unprejudiced" to be considerably larger than effective research would reveal. Moreover, the number who present themselves as unprejudiced probably exceeds considerably the number who honestly, though often inaccurately, see themselves in this light. Most indirect techniques for the measurement of attitudes have their rationale in observations such as these. The instrument to be described here is not, however, indirect in the usual sense of the word; it does not seek responses to items apparently unrelated to the attitudes investigated. We do, however, seek to measure prejudice in a manner less direct than is true of the usual prejudice scale. In our instrument we seek to measure anti-Negro prejudice. Persons are called upon to respond on social distance scales to whites and Negroes who occupy a variety of occupational positions. The measure of prejudice is derived through the summation of the differences in distance responses to Negroes as opposed to whites in the same occupations. Thus, for lack of a better label,
12,492 citations
Book•
01 Jul 1980
TL;DR: The application of item response theory to practical testing problems is discussed in this article, where the authors present an example of the application of the theory to real-world testing problems in a practical setting.
Abstract: Applications of Item response theory to practical testing problems , Applications of Item response theory to practical testing problems , کتابخانه مرکزی دانشگاه علوم پزشکی تهران
4,701 citations
"Personalized e-learning system usin..." refers methods in this paper
...Item Response Theory, IRT (Baker, 2001; Baker & Frank, 1992; Hambleton, 1985; Horward, 1990; Hulin, Drasgow, & Parsons, 1983; Hsu & Sadock, 1985; Lord, 1980 Wang, 1995), is a robust theory in education measurement....
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...Item Response Theory usually is applied in the Computerized Adaptive Test (CAT) domain (Baker, 2001; Baker & Frank, 1992; Hambleton, 1985; Horward, 1990; Hsu & Sadock, 1985; Hulin et al., 1983; Lord, 1980; Wang, 1995) to select the most appropriate items for examinees based on individual ability....
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TL;DR: It is explained how a hybrid system can incorporate the advantages of both methods while inheriting the disadvantages of neither, and how the particular design of the Fab architecture brings two additional benefits.
Abstract: The problem of recommending items from some fixed database has been studied extensively, and two main paradigms have emerged. In content-based recommendation one tries to recommend items similar to those a given user has liked in the past, whereas in collaborative recommendation one identifies users whose tastes are similar to those of the given user and recommends items they have liked. Our approach in Fab has been to combine these two methods. Here, we explain how a hybrid system can incorporate the advantages of both methods while inheriting the disadvantages of neither. In addition to what one might call the “generic advantages” inherent in any hybrid system, the particular design of the Fab architecture brings two additional benefits. First, two scaling problems common to all Web services are addressed—an increasing number of users and an increasing number of documents. Second, the system automatically identifies emergent communities of interest in the user population, enabling enhanced group awareness and communications. Here we describe the two approaches for contentbased and collaborative recommendation, explain how a hybrid system can be created, and then describe Fab, an implementation of such a system. For more details on both the implemented architecture and the experimental design the reader is referred to [1]. The content-based approach to recommendation has its roots in the information retrieval (IR) community, and employs many of the same techniques. Text documents are recommended based on a comparison between their content and a user profile. Data
3,175 citations
Book•
01 Jan 1972
TL;DR: In this paper, the authors present a survey of statistical and data analysis methods for probability distributions and their application to statistical quality control problems, including one and two Sided Tests of Hypotheses.
Abstract: 1. Introduction to Statistics and Data Analysis 2. Probability 3. Random Variables and Probability Distributions 4. Mathematical Expectations 5. Some Discrete Probability Distributions 6. Some Continuous Probability Distributions 7. Functions of Random Variables (optional) 8. Fundamental Distributions and Data Description 9. One and Two Sample Estimation Problems 10. One and Two Sided Tests of Hypotheses 11. Simple Linear Regression 12. Multiple Linear Regression 13. One Factor Experiments: General 14. Factorial Experiments (Two or More Factors) 15. 2k Factorial Experiments and Fractions 16. Nonparametric Statistics 17. Statistical Quality Control 18. Bayesian Statistics
2,945 citations