Designing and Developing a Novel Hybrid Adaptive Learning Path Recommendation System (ALPRS) for Gamification Mathematics Geometry Course

Abstract

Since recommendation systems possess the advantage of adaptive recommendation, they have gradually been applied to e-learning systems to recommend subsequent learning content for learners. However, problems exist in current learning recommender systems available to students in that they are often general learning content and unable to offer personalized service. To overcome this, in the context of a learning style based on an Interpretive Structural Model (ISM), an adaptive learning path recommendation system is proposed comprising: (a) Fuzzy Delphi Method, (b) Fuzzy ISM and (c) Kelly Repertory Grid Technology. The results show that the learning outcome with ALPRS is better than those from general learning course guided recommendation mechanisms, and the scores of system satisfaction with ALPRS and personal service are higher than 90%. Results of recall (95%), precision (68%), F1 index (45%) and MAE (8%) prove that ALPRS outperforms other approaches. Finally, three contributions are offered in this study:(1) a novel hybrid ALPRS is proposed and its practicability is tested; (2) a prototype gamification geometry-teaching material module is developed for the promotion in MSTE (Mathematics, Science and Technology Education) areas; (3) the adaptive geometry-learning path diagram generated with ISM based on learning styles could offer a basis for further studies.

Exploring Sustainability Environment Educational Design and Learning Effect Evaluation through Migration Theory: An Example of Environment Educational Serious Games

“…environmental education: (1) environmental awareness and understanding of the environment; (2) environmental conceptual knowledge; (3) environmental values and attitudes; (4) environmental action skills; and (5) environmental action experience. A design of hands-on simulated learning activities, compared with environmental education learning methods in traditional teaching textbooks, can significantly improve students' environmental education learning outcome, which is consistent with the results of various studies [76][77][78][79][80].…”

“…(2) environmental conceptual knowledge; (3) environmental values and attitudes; (4) environmental action skills; and (5) environmental action experience. A design of hands-on simulated learning activities, compared with environmental education learning methods in traditional teaching textbooks, can significantly improve students' environmental education learning outcome, which is consistent with the results of various studies [76][77][78][79][80]. environmental education: (1) environmental awareness and understanding of the environment; (2) environmental conceptual knowledge; (3) environmental values and attitudes; (4) environmental action skills; and (5) environmental action experience.…”

“…(1) In the future, the gamification environmental education App learning system may be used to assist experiential learning of various subjects and curricula to explore their impact on the learning outcomes and learning interests of different learning objects. Gamification learning has been experimentally studied in natural sciences, education of historical monuments, arts education in museums, and engineering simulation learning to prove that it can enhance learning outcomes and interest in learning, echoing the findings of past scholars [78][79][80]. In the future, it may be applied in different learning fields and learning subjects to explore its role in promoting learning outcome and performance.…”

The Effect of Users’ Behavioral Intention on Gamification Augmented Reality in Stem (Gar-Stem) Education

“…Gamification is designed to adapt enjoyable and interesting game elements to the activities being publicized. Applying these elements to teaching strengthens learning motivation (Su & Cheng, 2015;Su, 2017;Su, 2018). The application of gamification to social activities is a highly pronounced category, especially in social network websites where people share their daily lives.…”

Recommender in AI-enhanced Learning: An Assessment from the Perspective of Instructional Design

“…In some cases, however, it seems that complex formalizations try to overcome the weaknesses of the underlying models. Some recommenders are based on sophisticated formalizations with several elements that would need a complex evaluation scheme: "In the context of a learning style based on an Interpretive Structural Model (ISM), an adaptive learning path recommendation system is proposed comprising: (a) Fuzzy Delphi Method, (b) Fuzzy ISM and (c) Kelly Repertory Grid Technology" (Su, 2017).…”