Huan-Yu Lin

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

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.

An Iterative, Collaborative Ontology Construction Scheme

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 Adaptive Test Sheet Generation Mechanism Using Genetic Algorithm

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.

Building a computer-assisted process planning system using the hierarchical case-based reasoning approach

With recent globalization development in manufacturing industries, the traditional manufacturing strategy, Economies of Scale, is not suitable to meet the current globalization market. A significant challenge for the manufacturing sector is how to efficiently design manufacturing processes to meet the product customization. Manufacturing process design knowledge, at the product-level, process-level, and machine-level, is difficult to be managed and adopted by most existing computer-assisted process planning systems due to flat case structures and one-shot adaptation manners. Therefore, in this paper, a Hierarchical Case-Based Computer-Assisted Process Planning (HCB-CAPP) system is proposed, where manufacturing process design knowledge is represented by hierarchical case trees to manage the multi-level knowledge. Additionally, an interactive, multi-level case tree adaptation mechanism is proposed to assist designers in recursively retrieving and adapting case trees from product-level to machine-level to reuse and integrate previous design knowledge. According to the experimental result, novice designers agreed that this mechanism could realistically facilitate the manufacturing process design.

Adaptively Learning and Assessing SPSS Operating Skills Using Online SPSS Simulator

Online questionnaire is an emerging method for social science researchers to perform their survey. Although there are many data analysis software tools nowadays, such as SPSS, SAS, and Excel etc., to assist the students in analyzing the data of their surveys. However, the intentions of users for using the software tools cannot be probed and utilized to help the users operating them, so it will cause many errors on the students’ analysis results due to the misusage of software and result in that learning how to use the data analysis software tools based upon the students’ intentions becomes very time-consuming. Moreover, because the software operating procedures of the students are not recorded, the teachers cannot find out the students’ misconceptions. In this paper, we acquire the knowledge of using SPSS software and then apply the Simulator Generator concept proposed in previous research to build an online web-based SPSS software simulator for the students to emulate the operating process of SPSS software. Based upon the acquired frequent patterns of misuse, the teacher can design action routines embedded in the simulator to instantly detect the frequent error action patterns and help the students to rectify their misconceptions. Moreover, the teacher can trace and analyze the students’ learning statuses according to the logs generated from online SPSS Simulator. Using Simulator Generator, writing grammar rules is essential, but it is not easy for teachers. The knowledge of using SPSS software are largely identical but with minor differences. Thus, an SPSS Functional Ontology is proposed according to the features of SPSS software and the corresponding grammar rules are constructed in this research. Teachers just need to do some minor adjustments on the differences and the action routines, and then the new simulator will be generated automatically.

Collaborative Interpretative Service Assisted Design System Based on Hierarchical Case Based Approach

Museum is the important learning environment, which assists learners to learn directly from objects and living, and its interpretative services play an important role in museums to help learners learn more about the exhibitions. However, the development of intelligent interpretative services is costly, time consuming, and needs many kinds of domain knowledge. How to provide a platform to help experts of different domain work collaboratively to reduce the construction cost of designing an intelligent interpretative service for new requirements is an important issue. Thus, we propose a Collaborative interpretative service assisted design system (CISAD), containing requirement integration process to assist designers to collaboratively determine the requirements of the new service, and intelligent query processor to reuse previous successful application from coarse-grained to fine-grained to improve the reliability and reduce the construction cost of the solution application. Finally, we show an example to describe the construction process of an interpretative service for elder people by CISAD.

Collaborative Production Machine Choice System Based on Hierarchical Case Based Reasoning

New cell phone styles and technologies developments are changing quickly. To improve the ability of competition for a company, a new designed cell phone has to be available in the market in the short time. Therefore, production processes including manufacturing machine choice for a new cell phone product have to be determined quickly. Facing the lack of information, it is difficult to choose manufacturing machines for a production process for a new product. Thus, this study proposed a Collaborative Production Machine Choice System (CPMCS) based on a hierarchical case based reasoning approach to solve the problem of machine choice for new cell phone production. A real interaction system is built up also to help users for machine choice in this study. Using non-fixed number of new product features, this system can advise suitable machines for users by case based reasoning approach and help users to find out the right machines for production in the short time.