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    The relationship between academic performance and motivation level in e-learning among Thailand university students
    (2020-03-01)
    Na, Kew Si
    ;
    Petsangsri, Sirirat
    ;
    Tasir, Zaidatun
    E-learning has been extensively implemented in universities and motivation is one of the important factors contributing the successful learning. However, few studies focus on the relationship between student motivation level and academic performance in e-learning. Therefore, we explored the relationship between motivation and academic achievement among students in Thai universities. 115 social science students filled in an instructional materials motivation survey and the data was analyzed by using SPSS software. The majority of students were found to have upper to medium motivation levels in e-learning. Further, there was a weak, positive correlation between motivation level and academic achievement, but it was not statistically significant. More results are discussed in this paper.
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    Reverse SQL question generation algorithm in the dblearn adaptive e-learning system
    (2019-01-01)
    Atchariyachanvanich, Kanokwan
    ;
    Nalintippayawong, Srinual
    ;
    Julavanich, Thanakrit
    Using a traditional e-learning system, when teaching structured query language (SQL) queries in classical classrooms help instructors, to improve the students' SQL skills and learning effectiveness. However several problems in using e-learning as a teaching and learning assistant remain-such as difficulties in differences in learning ability and knowledge level. We solved these problems by applying an adaptation module to our e-learning system. However, we still found it required considerable effort to create enough exercises to make the adaptation effective enough. So, we developed a novel automatic question generating algorithm, named Reverse SQL Question Generation Algorithm (RSQLG), to automatically generate exercises (including both answer and question) from a source database. RSQLG reverses the traditional manual process used previously by instructors. Instead of creating questions and answers for them, RSQLG creates the answers first. The generated exercises are presented to students by applying question adaptation methodology based on student knowledge level in each supported learning objective. We evaluated the learning effectiveness of our approach by using outcome-based learning. After post-Test to pre-Test scores were compared, we found students using our system improved their scores by 26%. Consequently, the adaptive e-learning framework using RSQLG could be applied in any adaptive or traditional e-learning for a database course to benefit the instructors leading to less effort in exercise management and to improve the learning outcome from the students allowing as much practice as they need.
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    DBLearn: Adaptive e-learning for practical database course - An integrated architecture approach
    (2017-08-29)
    Nalintippayawong, Srinual
    ;
    Atchariyachanvanich, Kanokwan
    ;
    Julavanich, Thanakrit
    In this paper, an integrated architecture approach in designing and developing a DBLearn web-based application is presented. The DBLearn system is a personalized and adaptive e-learning system designed especially for learning practices in database courses. This approach focused on topics that are important but difficult for new learners, such as database design and structured query language (SQL) command query. The concept of adaptive e-learning and autonomous agents were applied in this system to eliminate the traditional constraints of effective e-learning, such as the problem of different learning sensory and knowledge levels. Four approaches were used to solve this problem. First, learning style theory was used to classify the way of learning for each student. Second, the student activity (historical data) is kept in the system to analyze the next knowledge the student should learn or review. Next, the SQL query automated grader was used to judge the correctness of the student's query. This grader supports all the necessary commands in both DML and DDL. Finally, the SQL query question generator module that can generate SQL query questions automatically is presented. This will reduce the instructor's work load in creating enough questions and allow the students to practice at their own pace as much as they want. By using these four techniques, the students will have a better learning experience and becoming more successful in learning outcomes.
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    What Makes university students use cloud-based e-learning?: Case study of KMITL students
    (2015-01-13)
    Atchariyachanvanich, Kanokwan
    ;
    Siripujaka, Nutchanon
    ;
    Jaiwong, Nattapong
    Cloud computing technology has been influential in overcoming problems in e-learning systems, such as the lack of scalability and storage limitation. Therefore, a framework for applying cloud computing on e-learning systems has been prepared. However, to develop a cloud-based e-learning system that matches well with the learners' needs and solves the current problems, it is important to know the learners' requirements. This research evaluated the key significant factors required for university students to use Cloud-based e-learning based on a research model, including the theory of motivation, and characteristics of cloud computing. In total, 250 students from King Mongkut's Institute of Technology Ladkrabang were surveyed by questionnaire. Data analysis was performed by factor and multiple regression analyses. Overall the factors that influence the intention to use cloud-based e-learning were identified as the availability, collaboration, cloud-based e-learning notifications, intrinsic motivation and extrinsic motivation. However, these account for only 62.9% of the usage intention, and so other factor(s) still remain to be determined.
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    A dynamic associative e-learning model based on a spreading activation network
    (2006-01-01)
    Nilas, Phongchai
    ;
    Nilas, Nilamit
    ;
    Mitatha, Somsak
    Presenting information to an e-learning environment is a challenge, mostly, because of the hypertext/hypermedia nature and the richness of the context and information provides. This paper proposes a dynamic semantic model for e-learning system based on the psycholinguistic theories of human memory; Spreading Activation Network (SAN). This work employs a SAN as a technique to provide the interface's action selection mechanism in an uncertain environment. The paper combines the SAN with the temporal logic to provide an e-learning system that a learning activity level evolves according to their expected contextual relevance. The system differs from the other e-learning by representing dynamic associations between learning activities and the relevance subjects. This system equipped with an Event-Triggered learning interface (context) adaptation component. This component provides multiple parallel processes for perception. These processes provide context screen selection and learning task operation based upon the user current situation. The SAN attempts to achieve a number of goals in an unpredictable complex dynamic environment. Spreading activation explains the predictive top-down effect of knowledge. It supports general heuristics which may be used as the first step of more elaborated methods. This model is suited to deal with the interaction between semantic and episodic memories, as well as many other practical issues regarding e-learning, including the retroactive effect of semantics over perception. The system uses the SAN to activate the most suitable interface screen (context) in response to the current conditions (learning activities) while the system continues working towards the learning objective goal. The paper presents our efforts to realize such e-learning system. The proposed paradigm has been implemented to develop a prototypical system, and the experiments also illustrate the robustness of such an e-learning framework.