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Evaluating Learning Success, Engagement, and Usability of Moalemy: An Arabic Rule-Based Chatbot

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Publicado en:Future Internet vol. 17, no. 10 (2025), p. 449-484
Autor principal: Al Faia Dalal
Otros Autores: Alomar Khalid
Publicado:
MDPI AG
Materias:
Teaching
Arabic language
Human-computer interaction
Usability
Success
Educational objectives
Learning outcomes
Chatbots
Academic achievement
User satisfaction
Personalized learning
Student participation
Research design
Effectiveness
Online instruction
Design of experiments
Customization
Morphology
Dialects
Adaptive learning
Efficiency
Teachers
Subjectivity
Distance learning
Internet
Rules
Prior knowledge
Computer assisted instruction > CAI
Satisfaction
Learning
Statistics
Acceso en línea:Citation/Abstract
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Resumen:A rule-based chatbot is a type of chatbot that responds by matching users’ queries with pre-defined rules. In e-learning, chatbots can enhance the learning experience by assisting teachers in delivering learning materials pleasantly. This research introduces Moalemy, an Arabic rule-based chatbot designed to provide a personalized learning experience by tailoring educational content to each learner’s prior knowledge. This empirical study evaluates learning outcomes, user engagement, and system usability using both subjective and objective metrics. It compares the effectiveness of a proposed Arabic rule-based chatbot with adaptive personalization to that of a static, non-personalized chatbot. The comparison was conducted across three levels of task difficulty (easy, medium, and hard) using a 2 × 3 within-subject experimental design with 34 participants. Descriptive statistics revealed higher mean values of usability and engagement in the adaptive method. Although the analysis revealed no significant variations in learning outcomes and SUS scores, it showed statistically significant differences in user satisfaction in favor of the adaptive method, p = 0.003. Analyses showed no significant differences between the two learning methods in terms of effectiveness, efficiency, and engagement. Across difficulty levels, the adaptive method outperforms the static method in terms of efficiency and effectiveness at the medium level, and in engagement at the easy level.
ISSN:1999-5903
DOI:10.3390/fi17100449
Fuente:ABI/INFORM Global