Adaptive Learning Technologies

With the rapid growth of technology, computer learning has become increasingly integrated with artificial intelligence techniques in order to develop more personalized educational systems. These systems are known as Intelligent Tutoring systems (ITSs). This paper focused on the variant characteristics of ITSs developed across different educational fields. The original studies from 2007 to 2017 were extracted from the PubMed, ProQuest, Scopus, Google scholar, Embase, Cochrane, and Web of Science databases. Finally, 53 papers were included in the study based on inclusion criteria. The educational fields in the ITSs were mainly computer sciences (37.73%). Action-condition rule-based reasoning, data mining, and Bayesian network with 33.96%, 22.64%, and 20.75% frequency respectively, were the most frequent artificial intelligent techniques applied in the ITSs. These techniques enable ITSs to deliver adaptive guidance and instruction, evaluate learners, define and update the learner's model, and classify or cluster learners. Specifically, the performance of the system, learner's performance, and experiences were used for evaluation of ITSs. Most ITSs were designed for web user interfaces. Although these systems could facilitate reasoning in the learning process, these systems have rarely been applied in experimental courses including problem-solving, decision-making in physics, chemistry, and clinical fields. Due to the important role of a cell phone in facilitating personalized learning and given the low rate of using mobile-based ITSs, this study has recommended the development and evaluation of mobile-based ITSs. ARTICLE HISTORY

This study aimed to investigate the effect of using McGraw-Hill Education (MGHE) Connect on students' academic performance. It examined the effects of MGHE Connect on the course letter grade, pass rate, retention rate, total score, and final exam score in addition to the proportions of having more A and B grades in the course. The study used a posttest-only control group design. The 95-student sample was selected by sampling four sections using a simple one-stage cluster method. Then two sections were randomly assigned as a treatment group (N=45), in which using MGHE Connect Chemistry was required to complete course assignments, quizzes, and tests, and the other two assigned as a control group (N=40) in which students completed the course conventionally. The study used ordinal logistic regression, binomial logistic regression, and multiple linear regression. The study indicated that when controlling the effect of students' CGPA, there was no significant difference in the odds of having higher letter grades between the experimental treatment and control groups. Also, the experimental group did not significantly have a higher proportion of A and B grades compared to the control group. The course pass rates and the retention rates in both groups differed insignificantly. The total course score and the course final exam score did not differ significantly. The study findings of students' academic performance metrics in the study indicating no statistically significant positive effect of the MGHE Connect on the student academic performance.

This systematic review of research on adaptive learning used a strategic search process to synthesize research on adaptive learning based on publication trends, instructional context, research methodology components, research focus, adaptive strategies, and technologies. A total of 61 articles on adaptive learning were analyzed to describe the current state of research and identify gaps in the literature. Descriptive characteristics were recorded, including publication patterns, instructional context, and research methodology components. The count of adaptive learning articles published fluctuated across the decade and peaked in 2015. During this time, the largest concentration of adaptive learning articles appeared in Computers and Education. The majority of the studies occurred in higher education in Taiwan and the United States, with the highest concentration in the computer science discipline. The research focus, adaptive strategies, and adaptive technologies used in these studies were also reviewed. The research was aligned with various instructional design phases, with more studies examining

Mobile Learning (M-Learning) is an emerging discipline in the area of education and educational technology. So researchers are trying to optimize and expanding its application in the field of education. The aim of this paper is to investigate the role of mobile devices and expert systems in disseminating and supporting the knowledge gained by intelligent tutors and to propose a system based on integration of intelligent M-Learning with expert systems. It acts as an intelligent tutor which can perform three processes-pre-test, learning concept and post-test-according to characteristic of the learner. The proposed system can improves the education efficiency highly as well as decreases costs. As a result, every time and everywhere (ETEW) simple and cheap learning would be provided via SMS, MMS and so on in this system. The global intention of M-Learning is to make learning "a way of being".

This paper will describe the development and implementation of an Adaptive System Prototype with the aim to manage an automated and customized learning experience. After the first in-depth study on the usefulness and effectiveness of personalized learning approach, the research team intended to fill the gap between the theory of personalized learning environments and its practice trough the development of an adaptive learning plugin implemented on mostly used, Open Source, Learning Management Systems. The developed technology, follow the goal to identify any end user of the LMS, create a customized user profile with their starting skills and learning preferences in order to automatically tailor a personalized learning path. The main purpose is to maximize student’s performance. This paper describes the main steps for the implementation of the prototype of this Adaptive Learning System named iO3 (intelligent Open Cube), as it will be an intelligent, Open Source, Open Learning, Open P...

Purpose The purpose of this paper is to work with Aboriginal and Torres Strait Islander people (ATSI), it is expected that non-ATSI health-care professionals become culturally aware; however, participants’ perceptions of the relative merit of cultural awareness training (CAT) formats is uncertain. Design/methodology/approach The authors compared undergraduate students’ perceptions of an asynchronous online format with onsite delivery formats of CAT using a mixed-method design. Students from five successive cohorts (n = 64) in an undergraduate programme were invited to complete a post-training survey which gathered quantitative and qualitative data. Findings Whilst feedback was positive regarding both formats, the onsite format was preferred qualitatively with several valuable learning outcome themes emerging from the results. These themes included; “perceived benefits of self-evaluation of students’ own culture whilst learning about Aboriginal culture”; “encouraging to be provided w...

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