Search results

Learning styles are incorporated more and more in e‐education, mostly in order to provide adaptivity with respect to the learning styles of students. For identifying learning styles, at the present time questionnaires are widely used. While such questionnaires exist for most learning style models, their validity and reliability is an important issue and has to be investigated to guarantee that the questionnaire really assesses what the learning style theory aims at. In this paper, we focus on the Index of Learning Styles (ILS), a 44‐item questionnaire to identify learning styles based on Felder‐ Silverman learning style model. The aim of this paper is to analyse data gathered from ILS by a data‐driven approach in order to investigate relationships within the learning styles. Results, obtained by Multiple Correspondence Analysis and cross‐validated by correlation analysis, show the consistent dependencies between some learning styles and lead then to conclude for scarce validity of the ILS questionnaire. Some latent dimensions present in data, that are unexpected, are discussed. Results are then compared with the ones given by literature concerning validity and reliability of the ILS questionnaire. Both the results and the comparisons show the effectiveness of data‐driven methods for patterns extraction even when unexpected dependencies are found and the importance of coherence and consistency of mathematical representation of data with respect to the methods selected for effective, precise and accurate modelling.

This paper aims to investigate the effect of learning styles on HyFlex learning towards equity of learning in higher education.

A quantitative approach was used, with data collection through a structured online questionnaire. The study participants were undergraduate students (n = 451) studying at various public and private universities in Indonesia. Measurement analysis is used to test the validity of the instrument used. Analysis of structural equations is used to test the relationships between the constructs under study.

Survey instruments have satisfactory internal validity and consistency. The learning style of students in higher education positively influences the use of HyFlex’s three learning modalities. All three modalities of HyFlex learning positively affect learning equity, especially the asynchronous online modality. However, the synchronous online effect is insignificant. Active/reflective learning styles only affect face-to-face mode but do not significantly affect the two online modalities, synchronous and asynchronous. Some of the learning style dimensions have an indirect effect on equity through three HyFlex learning modalities. Face-to-face and online asynchronous mediate well the indirect relationship between learning style and equity. The impact of gender and higher education status was not shown to strengthen the relationship between learning styles, HyFlex learning modalities and equity.

This study will provide valuable understanding for lecturers, educators and developers to adapt and develop HyFlex learning strategies based on the positive dimensions of the Felder–Silverman learning style that can support equitable and inclusive learning. The study forms a foundation for researchers to investigate more constructs that could improve HyFlex learning in future studies.

This research is a pioneer in using learning styles to investigate trends in using three HyFlex learning modalities, particularly emphasising modalities that can provide equitable learning.

The purpose of this study is to conduct a systematic review to understand state-of-art research related to learning preferences from the aspects of impacts, influential factors and evaluation methods.

This paper uses the systematic synthesis method to provide state-of-the-art knowledge on learning preference research by summarizing published studies in major databases and attempting to aggregate and reconcile the scientific results from the individual studies. The findings summarize aggregated research efforts and improve the quality of future research.

After analyzing existing literature, this study proposed three possible research directions in the future. First, researchers might focus on how to use the real-time tracking mechanism to further understand other impacts of learning preferences within the learning environments. Second, existing studies mainly focused on the influence of singular factors on learning preferences. The joint effects of multiple factors should be an important topic for future research. Finally, integrated algorithms might become the most popular evaluation method of learning preference in the era of smart learning environments.

This review used the search results generated by Google Scholar and Web of Science databases. There might be published papers available in other databases that have not been taken into account.

The research summarizes the state-of-art research related to learning preferences. This paper is one of the first to discuss the development of learning preference research in smart learning environments.

The purpose of this paper is to identify a framework to support adaptivity in e-learning environments. The framework reflects a novel hybrid approach incorporating the concept of the event-condition-action (ECA) model and intelligent agents. Moreover, a system prototype is developed reflecting the hybrid approach to supporting adaptivity in any given learning management system based on learners’ learning styles.

This paper offers a brief review of current frameworks and systems to support adaptivity in e-learning environments. A framework to support adaptivity is designed and discussed, reflecting the hybrid approach in detail. A system prototype is developed incorporating different adaptive features based on the Felder-Silverman learning styles model. Finally, the prototype is implemented in Moodle.

The system prototype supports real-time adaptivity in any given learning management system based on learners’ learning styles. It can deal with any type of content provided by course designers and instructors in the learning management system. Moreover, it can support adaptivity at both course and learner levels.

To the best of the authors’ knowledge, no previous work has been done incorporating the concept of the ECA model and intelligent agents as hybrid architecture to support adaptivity in e-learning environments. The system prototype has wider applicability and can be adapted to support different types of adaptivity.

Affective states in learning have gained immense attention in education. The precise affective-states prediction can increase the learning gain by adapting targeted interventions that can adjust the changes in individual affective states of students. Several techniques are devised for predicting the affective states considering audio, video and biosensors. Still, the system that relies on analyzing audio and video cannot certify anonymity and is subjected to privacy problems.

A new strategy, termed rider squirrel search algorithm-based deep long short-term memory (RiderSSA-based deep LSTM) is devised for affective-state prediction. The deep LSTM training is done by the proposed RiderSSA. Here, RiderSSA-based deep LSTM effectively predicts the affective states like confusion, engagement, frustration, anger, happiness, disgust, boredom, surprise and so on. In addition, the learning styles are predicted based on the extracted features using rider neural network (RideNN), for which the Felder–Silverman learning-style model (FSLSM) is considered. Here, the RideNN classifies the learners. Finally, the course ID, student ID, affective state, learning style, exam score and course completion are taken as output data to determine the correlative study.

The proposed RiderSSA-based deep LSTM provided enhanced efficiency with elevated accuracy of 0.962 and the highest correlation of 0.406.

The proposed method based on affective prediction obtained maximal accuracy and the highest correlation. Thus, the method can be applied to the course recommendation system based on affect prediction.

The purpose of this study is to examine learning style instruments used in Arab countries to measure higher education students’ learning styles, identify the most common instruments and determine whether the reliability and validity of these instruments have been verified in Arab contexts.

A comprehensive review of the existing literature using several databases and search engines. Descriptive statistics, such as frequencies and percentages were used to present the results.

There are only a few published studies related to learning styles in Arab countries, with the majority published between 2012 and 2016 using samples drawn from Saudi Arabia, the United Arab Emirates and Iraq. The most common learning style instrument is the Felder–Silverman/Solomon Index of Learning Styles. The reliability and validity of this instrument require further investigation.

This study is not without limitations. First, it covers only publications in the English language. Second, the paper focuses on research involving higher education students. Third, only research that was available online was used in this study. Nonetheless, the findings have several implications for researchers, educators and human resource development managers. For researchers, this study highlights research gaps that need to be filled. It also serves as a basis for more analytical and in-depth studies. The data also helps educators become more informed about the learning style instruments commonly used in the Arab context and whether the results from these instruments are dependable. Human resource development managers can draw on these findings to choose instruments that have proven reliable and valid.

This study is the first attempt to examine learning style instruments used in Arab countries and to explore whether the reliability and validity of these instruments have been verified in Arab contexts. This paper is a useful contribution to research into learning styles and learning style instruments.

This article outlines how an existing information literacy (IL) course was developed and embedded into a Learning Management System (LMS) with the aim of creating a blended learning environment for the course. It outlines how the platform was chosen, choice of learning design (LD) approaches, tools and processes used, Open Educational Resources (OERs) incorporated, the choice of Creative Commons (CC) licensing, branding, usage options and formats of materials.

A mixed-method approach was used in conducting this research. The online course was piloted in 2017 with two groups of students who completed an online questionnaire to provide their evaluation and feedback.

The results showed a very positive evaluation by the students, which shows that the university is on the correct path with embedding IL into a learner management system.

The author could not have the second face-to-face class with group 1 as was intended due to the student unrest at the university during this time. Also, with the disruption to the academic programme, the author had less feedback from students than expected; however, the 20% response rate was sufficient to inform the author’s future developments.

The flexibility (not a one size fits all) in usage was relevant and necessary to accommodate a number of student needs and socio-economic factors.

This article adds value to the academic project by showing how IL courses can successfully be embedded within an LMS, student preferences and socio-economic factors to be considered in a South African context.

The purpose of this study is to introduce a virtual collaborative learning setting called “Net Economy”, which we established as part of an international learning network of currently six universities, and present our approach to continuously improve the course in each cycle.

Using the community of inquiry framework as guidance and canonical action research (CAR) as the chosen research design, the discussion forum of the online course is assessed regarding its critical thinking value. We thereby measure critical thinking with the help of the according model provided by Newman et al. (1995), which differentiates 40 indicators of critical thinking from 10 different categories.

The calculated critical thinking ratios for the analyzed two discussion threads indicate a strong use of outside knowledge, intensive justification and critical assessment of posts by the students. But at the same time, there are also weak spots, like manifold repetitions. Based on these results, we derive changes for the next course cycle to improve the critical thinking of the students.

A comparison of the results after the next course cycle will then allow us to assess the effects of the implemented changes, which would not be possible without a critical thinking diagnosis approach.