Assessment and Learning in Knowledge Spaces (ALEKS) Adaptive System Impact on Students’ Perception and Self-Regulated Learning Skills

Harati, Hoda; Sujo-Montes, Laura; Tu, Chih Hsiung; Armfield, Shadow J.W.; Yen, Cherng Jyh

doi:10.3390/educsci11100603

Cited by 15 publications

(10 citation statements)

References 37 publications

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“…These measures could help improve communication flows and increase student satisfaction. These results agree with those of Schwanenberger et al [14] and Harati et al [13], who demonstrated that administrative officers need to improve their technological support to offer optimal communication to the student [19]. Furthermore, this could help free teachers from administrative functions and allow them to focus on their teaching tasks [1,3,12].…”

Section: Discussionsupporting

confidence: 88%

“…Sosa Díaz et al [4] and Van-Der-Velde et al [12] studied student satisfaction in the online classroom, concluding that communication skills through ICTs are necessary in the learning process both for accessing training content and to ensure optimal communication between the student and the other university worker's profiles-mainly lecturers and administrative staff. This opinion is shared by Harati et al [13] and Schwanenberger et al [14], who observed it both in students and in university administrative officers in online teaching. Obtaining timely feedback from lecturers in the evaluation process was crucial for students during online education in the pandemic period [15][16][17].…”

Section: Communication In He In the Pandemic Period: Literature Reviewmentioning

confidence: 89%

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An Organizational Model of Online Learning in the Pandemic Period: Comparison with Traditional Face-to-Face Learning

et al. 2022

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The COVID-19 pandemic has led to a paradigm shift in educational systems. During the lockdown, higher education became digital. This caused a change in communication within the educational ecosystem. Relational coordination (RC) is a communication and relationship model associated with the improvement of organizational results. Therefore, the objective of this research is to build an organizational model of online learning applied during the pandemic period and compare it with the previous face-to-face learning. A sample of 2774 students from two Ecuadorian universities was selected. A two-stage methodology was applied: First, an organizational model of online learning was built using multivariate methods. The RC model was linked to student satisfaction using generalized linear models (GLM). In the second stage, the organizational differences between the 2018 face-to-face and the 2020 online learning were identified. Finally, the online learning model was validated with external data. The components associated with a higher level of RC were institutional cooperation, institutional problem-solving, and administrative communication. Administrative communication lost importance in the online model. Significant differences between the satisfaction of the two models were not found. Nevertheless, since online learning was not associated with an improvement in satisfaction, the creation of a third educational model that combines the best practices of online and face-to-face learning in a hybrid system could be an alternative that improves the satisfaction of students.

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Section: Discussionsupporting

confidence: 88%

Section: Communication In He In the Pandemic Period: Literature Reviewmentioning

confidence: 89%

An Organizational Model of Online Learning in the Pandemic Period: Comparison with Traditional Face-to-Face Learning

et al. 2022

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“…The developed adaptive learning management system, namely Dyslexia Adaptive E-Learning Management System (DAELMS), proves that when the system provides the user with learning materials that match their learning style or dyslexia type, it improves their learning outcomes (Alsobhi et al, 2019). This adaptive learning system was also discussed in research that had been done by (Kazimzade, et al, 2019;Picciano, 2019;Harati et al, 2021). Meanwhile, Krechetov and Romanenko (2020) has proposed a genetic algorithm to exploit adaptive learning technology and technique to create an autonomous system of teacher-less learning as an effective student profiling tool in e-learning, providing teachers with extensive student performance analytics and allowing them to adjust individual learning paths.…”

Section: Adaptive Learningmentioning

confidence: 90%

“…When there is no direct access to in-person instructors, adaptive learning, as a new form of online learning, can focus on the needs of each learner and assist them with their learning process by adapting learning materials based on their knowledge level and personalizing their learning path (Harati et al, 2021).…”

Section: Adaptive Learningmentioning

confidence: 99%

Trends on Technologies and Artificial Intelligence in Education for Personalized Learning: Systematic Literature Review

Hashim¹,

Omar²,

Jalil³

et al. 2022

IJARPED

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The continuous development of new technology and rapid advancement of Artificial Intelligence (AI) contribute to the improvement and enrichment of the teaching and learning process. AI technology promotes a flexible, customized, and effective learning environment, as well as improves other educational competencies via personalized learning. To create a personalized learning environment, AI collects, compiles, and interprets data from a variety of sources to create student learning profiles. However, a lack of information exists on incorporating AI technology into educational settings to promote teaching efficiency in Malaysia. AI technology helps to predict how well students will learn, so we can make content that is tailored to each person's goal and past success. To gain a better understanding of the concept and implementation of a personalized learning environment employing AI technology, a systematic literature review (SLR) was conducted to identify the trends of technologies and Artificial Intelligence in Education (AIEd) in promoting personalized learning. SLR has become the standard methodology for identifying answers by tracing the outcomes of past research by identifying and synthesising significant findings using systematic, transparent and repeatable techniques at each stage of the process. The literature search was performed in SCOPUS and Web of Sciences WoS) database and thirty-two articles from the years 2016 to 2022 were initially reviewed. From this number, 14 articles were included for analysis. Based on the findings, most learning elements, such as technology, teaching approach, teaching content can be adapted to each student's needs and learning intent in personalized learning. Personalised learning using AI is an approach that focuses on generating training to match the specific needs of each student such as in adaptive learning, online learning, MOOCs, and many other technologies. A few approaches on the other hand, appear to witness technological advancement as providing opportunities for individualised learning by applying analytical tools and algorithms to create automated adaptive learning activities and materials. The study of technologies for personalized learning in education in other nations has primarily concentrated on higher education, and it is advised that the scope of the research be expanded. In Malaysia. the implementation of these technologies in education should be bolstered. The research and practices reported in the study also show

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“…All students enrolled in GC1 were directed to complete the ALEKS initial knowledge check in the weeks leading up to the start of the semester. During the adaptive knowledge check, ALEKS accurately assessed student knowledge of all the topics included in the course (209 topics total, on average), and prepared each student’s custom learning pathway. − Of the topics that were included in ALEKS, roughly half were considered by the course instructors to be prerequisite and foundational for GC1 (approximately 100 topics). Students were expected to demonstrate mastery of these prerequisite topics during the initial knowledge check or to work in ALEKS to learn these topics before the start of the semester.…”

Section: Methodsmentioning

confidence: 99%

Examining Educational Debts in Student Preparation for General Chemistry

Caushi,

Torres,

Abrams

2024

J. Chem. Educ.

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Students beginning college chemistry are expected to arrive prepared with fundamental, prerequisite conceptual understanding and skills from high school. While some topics may be reviewed explicitly in the course, prerequisite material�including hidden prerequisites often overlooked by faculty�is typically considered assumed prior knowledge and not taught in General Chemistry. This study examines the correlation between preparedness in fundamental topics and success in first-semester General Chemistry. The examined content areas included math and physics, measurement, matter, atoms/ ions/molecules, stoichiometry, basics of chemical reactions, thermodynamics, electronic structure, and bonding. Five areas (math and physics, measurement, matter, atoms/ions/molecules, and stoichiometry) positively correlated with success in General Chemistry, highlighting potential focus areas for resources to support students. Following the tenets of Quantitative Critical Race Theory, this study identified and quantified educational debts in preparation owed to students from historically marginalized groups. As a result of the pervasive effects of systemic injustices encountered by students from these groups, educational debts were observed in all prerequisite areas that correlated with student success. Moreover, these debts increased through the course, even when controlling for preparation. Specifically, Black and Hispanic students faced the largest educational debts in final course grades, with Black students receiving half of a letter grade lower than their White peers and Hispanic students receiving a third of a letter grade lower. These results emphasize the importance of addressing systemic barriers to reduce educational debts and providing constructive interventions to best prepare students and promote equitable outcomes.

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Assessment and Learning in Knowledge Spaces (ALEKS) Adaptive System Impact on Students’ Perception and Self-Regulated Learning Skills

Cited by 15 publications

References 37 publications

An Organizational Model of Online Learning in the Pandemic Period: Comparison with Traditional Face-to-Face Learning

An Organizational Model of Online Learning in the Pandemic Period: Comparison with Traditional Face-to-Face Learning

Trends on Technologies and Artificial Intelligence in Education for Personalized Learning: Systematic Literature Review

Examining Educational Debts in Student Preparation for General Chemistry

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