Academic journal article Educational Technology & Society

A Social Learning Management System Supporting Feedback for Incorrect Answers Based on Social Network Services

Academic journal article Educational Technology & Society

A Social Learning Management System Supporting Feedback for Incorrect Answers Based on Social Network Services

Article excerpt

Introduction

With the development of the Internet, a considerable amount of research has been carried out on Web-based e-learning, which enables learners to study anytime and anywhere without traditional limitations of place and time (Horton, 2000). In addition, a variety of learning management systems (LMSs) has been developed for the systematic management of courses, grades, progress, and attendance of the students. Representative examples of LMSs include Moodle (Cole & Foster, 2007; Kumar, Gankotiya, & Dutta, 2011), Desire2Learn (D2L) (Wang, & Shao, 2008), and Blackboard (Martin, 2008; Pishva, Nishantha, & Dang, 2010). LMSs support and manage learning content allowing various file formats and media. One of the various features of LMSs is the ability to conduct assessment by providing learners with a quiz (or tests) to evaluate their ability, analyze their correct or incorrect answers, and provide feedback on their incorrect answers. The quiz helps learners recognize the information they did not understand during the learning period. An educator can evaluate a learner's grade by using learners' quiz results. In particular, feedback, including an explanation of incorrect answers, helps learners improve their understanding of the learning contents and relearn why their answers were incorrect (Thoms, 2011).

However, the quiz and feedback of existing LMSs has the following limitations: a lack of analysis of whether the learners understand the content; static explanations despite the different learning abilities of the respective learners; and restricted interaction and collaboration feedback among learners. First, existing LMSs lack the ability to analyze whether learners understand the precise meaning of a question. Such systems simply measure the level of understanding and insight of learners by depending on the outcome of analyzing their correct or incorrect quiz answers. Some correct answers may have been given by chance, but the learners are not provided with an explanation and feedback for such answers. To improve the learner's understanding of the subject material and evaluate their level of understanding and insight, an LMS system needs to be able to analyze whether the learner correctly understands the questions and answers of a quiz. In addition, existing LMSs only provide a previously defined static explanation of an incorrect answer without analyzing the various reasons why the learners may have answered a question incorrectly. Analyzing the various causes for incorrect answers and providing a corresponding explanation require considerable time and cost. To solve incorrect answers, the learners study and acquire additional information from the internet or the course lectures, or ask the educator or someone despite providing basic static explanation. This additional inconvenient process is frequently repeated. As a result, refinement and further development of LMSs is required for efficiently supporting and managing various analyses based upon the causes of incorrect answers and the different levels of learner achievement. Finally, as a general course-based approach to e- learning, such systems have restricted interaction and collaboration feedback among learners (Dalsgaard, 2007). When a learner has a question related to a course lecture, the learner may ask the educator during the course. The educator can provide feedback to the learners through different questions and lead the students through the course. On the other hand, the relationship among learners is temporary and restricted to the duration of the course. After the end of the course period, the learners may not have the opportunity to ask questions related to their learning. As a result, these limitations make an LMS inappropriate for supporting collaborative learning.

Various researches in education investigating interaction, participation, and sharing among learners have been recently conducted with the evolution of Web 2. …

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