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Top1. Introduction
Current Internet technology allows students to learn at any time and in any place and to use time and space effectively and to significantly enhance the flexibility of the learning environment. Teachers in an online learning environment interact with students by the Internet, and thus, cannot observe students’ learning reactions directly. Therefore, the online-learning field should continuously strive to allow teachers to control of student learning situations, recognize students’ lack of capability in a course, and implement a preventive and remedial learning strategy to enhance student learning effectiveness.
Online learning platforms record complete student information and are based on function and themes. For instance, the platforms record course grades of students or complete online information. A teacher who reviews a student’s learning situation must examine the students’ learning records according to different items, and further organize and define the students’ current learning situations, which is inconvenient for the teacher.
Thus, to enable convenient reviews of student situations by teachers, this study provides an integrated analytical tool and acquires specific student information from a vast and rich online learning platform. Following observation and diagnosis of learning feature, this study realizes that teachers cannot thoroughly control the varied learning situations of students. Student abilities are the most abstract. Thus, this study includes the diagnosis of learning content in its observation and diagnosis of multidimensional learning features. Using learning portfolio, knowledge structure and ability indicators, the researcher probes students learned in the course. Based on an observation and diagnosis of multidimensional learning features, this work develops an On-Line Learning Analyzing and Diagnosing System (OLADS).
The design concept of the inquiry interface is based on the interface similar to natural language to allow teachers to integrate required information more instinctively. Teachers without a database background can easily find students who do not match the ability indicators or have abnormal learning. For helping teacher to know learning situation of students, this study proposes a new diagnosis and remedial strategy for on-line learning.
The learning activities in OLADS include three stages: self-learning stage, mutual learning stage and guidance stage. At the self-learning stage, students are learning individually. The proposed system collects and diagnoses students’ learning situation with knowledge structure, learning portfolio and ability indicators. Teachers and students can obtain the last learning situation by using OLADS at any moment. At the mutual learning stage, the proposed system allocates students with complementary learning features in the same learning group for mutual learning. Few students might not progress in the self-learning and mutual learning stages. At the guidance stage, teachers can review student learning by the student information function and recognize their learning situations according to individual and overall learning information the system provide to establish proper plans for remedial learning. At self-learning stage, students are in independent learning, and students have different learning features because their characteristics are varied. The first stage of self-learning collects the learning features of student. To enhance their learning features that are lacking at the self-learning stage, the researcher proposes the mutual learning stage. Students with abnormal situations enter the guidance stage.
The rest of this paper is organized as follows. Section 2 introduces background and purpose of this study. Section 3 introduces three observation and diagnosis tools, learning portfolio, knowledge structure and ability indicators, which provide the basis of this study. In section 4, the three tools are applied to learning activities with Multi-stage guided remedial learning strategy. Meanwhile, section 5 presents the evaluation results and statistical analysis. Finally, conclusions and future research directions are presented in Section 6.