On Educational psychology: A cognitive view.

This review pursues a twofold goal, the first is to preserve and enhance the chronicles of recent educational data mining (EDM) advances development; the second is to organize, analyze, and discuss the content of the review based on the outcomes produced by a data mining (DM) approach. Thus, as result of the selection and analysis of 240 EDM works, an EDM work profile was compiled to describe 222 EDM approaches and 18 tools. A profile of the EDM works was organized as a raw data base, which was transformed into an ad-hoc data base suitable to be mined. As result of the execution of statistical and clustering processes, a set of educational functionalities was found, a realistic pattern of EDM approaches was discovered, and two patterns of value-instances to depict EDM approaches based on descriptive and predictive models were identified. One key finding is: most of the EDM approaches are ground on a basic set composed by three kinds of educational systems, disciplines, tasks, methods, and algorithms each. The review concludes with a snapshot of the surveyed EDM works, and provides an analysis of the EDM strengths, weakness, opportunities, and threats, whose factors represent, in a sense, future work to be fulfilled.

https://romisatriawahono.net/lecture/rm/survey/machine%20learning/Ayala%20-%20Educational%20Data%20Mining%20-%202014.pdf

Review: Educational data mining: A survey and a data mining-based analysis of recent works

Simple Object Access Protocol と,その応用としてのソフトウェアの組み合わせについて (渡邉昭夫教授退任記念号)

To provide customized workplace learning opportunities, a digital badge system was designed by a university, governmental agency and national professional association to support teachers' implementation of professional development ( PD). Teacher Learning Journeys ( TLJ) is an approach that allows for teachers to customize their PD experience to their workplace and make decisions about what PD they need based on their expertise and interests. The digital badging provided and assessed experiences in online PD. Using a theoretical framework that focused on decision making and customization as part of personalization, researchers conducted a theory-driven thematic analysis on teachers' TLJ artifacts (goal statements, interviews and reflective activity logs). Data came from 36 teachers who completed 154 PD activities over a 3-month period. A JOUR study was developed from an in-depth analysis of eight teachers' artifacts and interviews. Using TLJ as a PD tool, teachers made decisions when selecting learning goals they identified as personally relevant. Teachers customized the level of assessment and the specific content depth to personalize the PD training for workplace constraints. This project informs future research aiming to understand how personalized learning activities support teachers and other professional learners in a variety of workplaces. [ABSTRACT FROM AUTHOR]

Personalized workplace learning: An exploratory study on digital badging within a teacher professional development program

Over the last decade, several research initiatives have investigated the potentials of the educational paradigm shift from the traditional one-size-fits-all teaching approaches to adaptive and personalized learning. On the other hand, mobile devices are recognized as an emerging technology to facilitate teaching and learning strategies that exploit individual learners' context. This has led to an increased interest on context-aware adaptive and personalized mobile learning systems aiming to provide learning experiences delivered via mobile devices and tailored to learner's personal characteristics and situation. To this end, in this paper we present a context-aware adaptive and personalized mobile learning system, namely the Units of Learning mobile Player (UoLmP), which aims to support semi-automatic adaptation of learning activities, that is: (a) adaptations to the interconnection of the learning activities (namely, the learning flow) and (b) adaptations to the educational resources, tools and services that support the learning activities. Initial evaluation results from the use of UoLmP provide evidence that UoLmP can successfully adapt the learning flow of an educational scenario and the delivery of educational resources, tools and services that support the learning activities. Finally, these adaptations can facilitate students to complete successfully the learning activities of an educational scenario.

ORIGINAL ARTICLE: Context-aware adaptive and personalized mobile learning delivery supported by UoLmP

With the heterogeneous proliferation of mobile devices, the delivery of learning materials on such devices becomes subject to more and more requirements. Personalized learning content adaptation, therefore, becomes increasingly important to meet the diverse needs imposed by devices, users, usage contexts, and infrastructure. Historical server logs offer a wealth of information on hardware capabilities, learners' preferences, and network conditions, which can be utilized to respond to a new user request with the personalized learning content created from a previous similar request. In this paper, we propose a Personalized Learning Content Adaptation Mechanism (PLCAM), which applies data mining techniques, including clustering and decision tree approaches, to efficiently manage a large number of historical learners' requests. The proposed method will intelligently and directly deliver proper personalized learning content with higher fidelity from the Sharable Content Object Reference Model (SCORM)-compliant Learning Object Repository (LOR) by means of the proposed adaptation decision and content synthesis processes. Furthermore, the experimental results indicate that it is efficient and is expected to prove beneficial to learners.

https://ir.nctu.edu.tw:443/bitstream/11536/9088/1/000288799600002.pdf

A personalized learning content adaptation mechanism to meet diverse user needs in mobile learning environments

Nowadays, ontology of subject knowledge is applied for intelligent e-learning to provide learners with adaptive learning guidance and efficient learning content management. However, it is difficult and costly to construct an ontology for a given domain even though using the GUI tools. Therefore, how to propose an easy way to acquire the knowledge of experts, how to integrate these diverse opinions of experts into the consensus, and how to incrementally refine and converge the ontology to maintain the most suitable one have been paid attention recently. Accordingly, in this paper, we propose an Iterative, Collaborative Ontology Construction (ICOC) scheme. In each iteration, our proposed wild-like online ontology editor can help users collaboratively contribute their knowledge. Next, it automatically generates an appropriate questionnaire to converge the opinions of users to a new version of ontology using a Delphi-like method. The convergence process stops when all the relations are converged or eliminated by the questionnaire analysis. According to this ICOC scheme, the created ontology can be more acceptable.

An Iterative, Collaborative Ontology Construction Scheme

With the development of e-learning technology, many specifications of instructional design have been proposed to make learning activity sharable and reusable. With the specifications and sufficient learning resources, the researches further focus on how to provide learners more appropriate learning activities to improve their learning performance. In this paper, we aim to propose a model which can explicitly represent the knowledge of the mechanism to adapt both the learning activity navigation and content presentation according to learners' knowledge of concepts. In our proposed model, each learning unit object contains the learning items and the related concepts, which can be used to perform adaptive content selection, and the sequencing control of these learning unit objects can be explicitly represented as a directed graph to improve the understandability. Based on the learning sequencing graph, an Object Oriented Learning Activity system is implemented and used to design and perform the learning activity of Scaffolding Instruction, named "The evaporation, condensation and boil of water". The Evaluation results show that teachers can effectively design an adaptive learning activity based on concept and misconception hierarchy and the designed learning activity can really improve learners' learning efficacy by the OOLA system.

https://www.jstor.org/stable/jeductechsoci.12.3.248

Design and Implementation of an Object Oriented Learning Activity System

Promoting the development of students’ scientific inquiry capabilities is a major learning objective in science education. As a result, teachers require effective assessment approaches to evaluate students’ scientific inquiry-related performance. Teachers must also be able to offer appropriate supplementary instructions, as needed, to students. Scientific inquiry capabilities should be assessed by evaluating students’ scientific inquiry portfolios in actual hands-on experiments. Although virtual laboratory systems can reduce the cost of conducting scientific inquiry experiments, the manual portfolio assessment approach is still difficult and time-consuming for teachers. Therefore, in this paper, in order to provide students with personalized learning guidance concerning not only the conceptual knowledge, but also the high-order, integrative abilities of scientific inquiry, an Online Portfolio Assessment and Diagnosis Scheme, called OPASS, was proposed to assist teachers in automatically assessing and diagnosing students’ abilities as they relate to scientific inquiry performance. Personalized diagnostic reports were generated by employing the rule-based inference approach, which diagnosed learning problems and provided corresponding reasons and remedial suggestions based on teacher-defined assessment knowledge of the scientific inquiry experiment. For the evaluation, experimental results showed that the OPASS was helpful and beneficial for both students and teachers.

/pdf/opass-an-online-portfolio-assessment-and-diagnosis-scheme-to-1cd8w5c267.pdf

OPASS: An Online Portfolio Assessment and Diagnosis Scheme to Support Web-Based Scientific Inquiry Experiments.

For test-sheet composition systems, it is important to adaptively compose test sheets with diverse conceptual scopes, discrimination and difficulty degrees to meet various assessment requirements during real learning situations. Computation time and item exposure rate also influence performance and item bank security. Therefore, this study proposes an Adaptive Test Sheet Generation (ATSG) mechanism, where a Candidate Item Selection Strategy adaptively determines candidate test items and conceptual granularities according to desired conceptual scopes, and an Aggregate Objective Function applies Genetic Algorithm (GA) to figure out the approximate solution of mixed integer programming problem for the test-sheet composition. Experimental results show that the ATSG mechanism can efficiently, precisely generate test sheets to meet the various assessment requirements than existing ones. Furthermore, according to experimental finding, Fractal Time Series approach can be applied to analyze the self-similarity characteristics of GA’s fitness scores for improving the quality of the test-sheet composition in the near future.

/pdf/an-adaptive-test-sheet-generation-mechanism-using-genetic-2ea0l2wzh3.pdf

Huan-Yu Lin

Papers

A personalized learning content adaptation mechanism to meet diverse user needs in mobile learning environments

An Iterative, Collaborative Ontology Construction Scheme

Design and Implementation of an Object Oriented Learning Activity System

OPASS: An Online Portfolio Assessment and Diagnosis Scheme to Support Web-Based Scientific Inquiry Experiments.

An Adaptive Test Sheet Generation Mechanism Using Genetic Algorithm