Web 3.0 – Based personalisation of learning objects in virtual learning environments

As the Covid 19 Pandemic greatly impacted teaching and learning, academic institutions switched from in-person to online classes. This shift prompted an examination of students’ learning styles to accommodate their learning in virtual environment. The VARK (Visual-Aural-Read/Write-Kinesthetic) instrument was used to assess effectiveness of teaching and students’ learning in U.S. Coast Guard Academy (CGA) undergraduate engineering course. The VARK instrument was used to facilitate effective virtual classroom activities to engineering students during the COVID-19 pandemic. This paper argues that students have different learning strengths and styles. Some students may learn best by watching and listening, others by thinking, and others by doing or by doing, touching, and feeling. Our results indicate that engineering students demonstrate a strong preference for at least two learning styles and the learning styles differ between male and female students. Females are not kinesthetic learners, but their preferable mode of learning is verbal or reading. Male students preferred aural style and African Americans kinesthetic learning style. This research was conducted to improve our teaching and provide students with safe learning environment during challenging time of the COVID-19 pandemic. The paper finds that learning styles are important across all majors during virtual learning and teaching. The VARK instrument can be used to indicate cadets’ learning styles to facilitate effective learning and teaching in virtual environment during the COVID-19 pandemic.

In todays global and high-tech economy, the primary contributing factor to sustainable competitive advantage is the strategic development of employees, an organizations only unique asset. However, with four generations actively present in the workforce and the proliferation of web-based learning as a key method for developing employees, corporate training has not kept pace with the needs of the 21st-century, generationally diverse employee population. This study used a quantitative and descriptive methodology to investigate differences in learning style preferences of the various generational cohorts. Three streams of literature informed this research including generational differences in learning preferences, existing and emerging technologies and learning activities in web-based training, and how learning style preferences can inform effective instructional design. A sample population of management employees at a publically traded railroad organization were asked to complete the Felder-Soloman Index of Learning Styles to identify their learning style preferences and to identify their preferred learning activities. The research study showed insignificant differences in learning style preferences of the different generations. In addition, there were insignificant differences in learning activity preferences. The results also showed learning styles corresponded closely with learning activity preferences. Surprisingly, there was a lack of interest in learning with Web 2.0 technologies, such as social media forums or twitter-like environments. This was particularly unexpected as it pertains to Millennials, who are typically known as the techno-generation. The key research question from this study was how can instructional design for web-based learning be optimized to address the learning style preferences of a generationally diverse workforce? The recommendation is that each student population be surveyed regarding learning style preferences and learning activity preferences before designing curriculum. Popular literature indicates that Web 2.0 technology is the future of learning and each generation has unique learning needs; however, this was not the case for this particular student population. As such, the stereotypes of generations in popular literature and the predictions of future learning trends should be considered carefully before creating new learning environments. Instructional designers should be cautious when making assumptions about generational differences.

In a student-centered teaching and learning environment, students' needs, potentials, and learning styles are considered crucial. Therefore, teachers need to understand what learning styles students prefer to teach effectively. In the current study, a quantitative research approach has been adopted in this study within it descriptive research designed was used. To determine the preferred learning styles of B.Ed. students, VARK (Visual, Aural, Read/Write, and Kinesthetic) learning style model has been used. Since the data was collected using the VARK questionnaire, simple random sampling techniques were used. The reliability of the instrument was calculated through Cronbach α= 0.75. The sample of the study consists of 140 Bachelor of Education (B.Ed.) students of a Public Sector University located in Northern Sindh, Pakistan. The data were analyzed through descriptive statistics (percentages mean and standard deviation) to determine the most preferred style of learning of students. The results of the study revealed that 27.93% of the B.Ed. students have preferred aural learning style, 25.13% kinaesthetic learning style, 22.65% visual style of learning and 21.09% preferred read/write learning style respectively. To conclude that the majority of the B.Ed. students preferred aural learning style and the least preferred style of learning was read/write. Hence, B.Ed. students were driven towards an aural learning style. This study suggests that students learning styles are influenced by the teacher’s teaching style. Therefore, the teacher can determine his/her teaching style by using the score of the VARK questionnaire. The study recommends that another study can be conducted by the teachers to learn about the larger number of students’ preferred learning styles. The teacher can also address a mixture of learning styles. In the classroom, there are always diverse learners. In that case, the teacher can use integrated teaching style which can address all learners preferred teaching style.

INTRODUCTION: Learning styles refer to the ways an individual processes and retain new information and skills. Knowledge about preferred learning styles can assist in developing effective pedagogies and enhance classroom–learning experiences. Optimal learning environments consider how students learn and utilize various teaching methods for curriculum delivery to match specified student learning preferences. METHODS: This cross-sectional study presents the findings of the preferred learning style of 97 physiotherapy students studying in JSS College of Physiotherapy, Mysuru, using a self-administered questionnaire developed by Victoria Chislett and Alan Chapman, 2005. Data were collected using the survey method through Google Forms. RESULTS: We found equal distribution of unimodal and multimodal learning style. Among the unimodal style of learning, 20.6% of participants had predominantly auditory learning style. 15.46% of participants had predominantly visual learning style. 10.3% of participants had predominantly kinesthetic learning style. In multimodal style of learning, 21.6% of participants had predominantly visual and auditory learning styles. 15.46% of participants had predominantly visual and kinesthetic learning style. 12.37% of participants had predominantly auditory and kinesthetic learning style and only 1% of participants had visual, auditory, and kinesthetic learning style. CONCLUSION: The most preferred unimodal learning style among physiotherapy students was auditory followed by visual and kinesthetic. The most preferred multimodal style of learning was visual and auditory, followed by visual and kinesthetic.

Objectives: To perform a gender analysis on the usage of Virtual Learning Environment (VLE) of simulation based e-learning in the field of Software Engineering in specific reference to the dynamic complexity, a modeling framework for Software Engineering Simulation based e-Learning Environment (SESeLE) tool is needed and has been proposed. Method/Statistical Analysis: A questionnaire based survey has been carried out twice on the learners enrolled in Computers and Information Technology based courses at tertiary levels in and around the city of Chandigarh in north India. The learners were provided an interactive single-learner environment of the SESeLE which was accessible through the internet by using a standard web-browser. In all, 392 students of tertiary level were included as subjects and were made to respond twice on the issues like their practical knowledge of software handling, interest and knowledge in software project management and impact of e-learning on their knowledge in software project management through questionnaire survey. The questionnaire was first got filled up from the subjects without any exposure to the SESeLE and subsequently after a training session on the SESeLE. ANOVA test was performed to find out the significant differences in various learning styles on post-training test scores overall and in both male and female students as well. Findings: This study is unique and one of its own kind. It has been used to analyse the impact of using VLE tools by the learners/students on their learning and also for the gender analysis on various parameters. The web based learning style has been found to be the most preferred learning style among female students and the second most preferred style of learning among male students. Reading textbooks was not significantly popular among female students as compared to male students. About half of the students agreed to participate in any kind of seminar on software project management. The post-training test score on the knowledge about typical patterns observed in software project management issues has been found to be significantly higher from pre-training test scores. No significant difference has been found among the average response of the male and female students on all issues related to their Interest in Software Project Management. The post-training test scores of male and female students on both the issues of simple and difficult software project management were significantly different; the pre- and post-training test scores of the students on both the issues were different significantly; and lastly, significant difference was found between the post-training test scores on both the issues among students categorized according to their preferred choice of learning. Application/Improvements: It will be interesting to evaluate, in future, the effectiveness of SESeLE for the learners.

Containerization: Practical infrastructure and accessibility efficiency for the Virtual Learning Environment 
 Context and motivation:
 Containers are transforming modern application infrastructure, providing advantages for accessibility and allow many instances of existing legacy applications to be run at the same time on the latest operating systems. This can implement an ideal virtual learning environment which offers a dynamic learning space where instructors upload activities and resources to enhance learning. The goal is to provide a structured learning environment suited to both the student and the instructor, where materials are easily accessed, and that many files can be transferred at one time. The system should cope with the demands of many students occupying the same virtual learning space, providing each student with individual learning experiences. There are challenges when instructors attempt to adapt the learning environment to meet the learning objectives. Technology barriers to the education provider, primarily in the form of high cost of technology infrastructure requirements need to be overcome before widespread adoption of a virtual learning environment is seen. The potential to overcome these barriers through the application of containerisation provides the motivation behind this presentation (Katz & Council of Independent, 2016; Puvaneswary & Siew Hwa, 2019).
 
 What will be demonstrated in this presentation?
 The use of containers provides the ability to supply many instances of the same application running on a single machine. Each instance is isolated, along with any associated dependencies, allowing efficient utilisation of system resources, such as processing and memory. The presentation will demonstrate how many instances of the same application can be activated and the resource advantages gained. The presentation will show a system that has been used to provide a complex structured virtual learning environment to level 7 students and discuss how the system was utilised to provide a positive, individualised learning experience to the students. Security and confidentiality is maintained within each containerized instance. The presentation will show how the system can be configured to be self-healing, respond to scheduling, and to automatically restart single instances as required.
 
 The implications for future practice
 The presentation will show how the advantages of containerization can be integrated at many levels of the virtual learning environment, providing many separate and individual instances of the same application. The number of instances can be easily adjusted as required, and resources are automatically allocated, reducing support overhead and cost of infrastructure. The implications are that each instance can provide a unique experience to each student, whilst reducing the workload of the instructor, and minimizing the cost to the education provider.
 
 
 References
 Katz, P. M., & Council of Independent, C. (2016). High-Tech or High-Touch? Online Learning and Independent Higher Education. Innovations in Teaching and Learning. Research Brief 5: Council of Independent Colleges. Retrieved from http://ezproxy.aut.ac.nz/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=eric&AN=ED569215&site=eds-live
 Puvaneswary, M., & Siew Hwa, Y. (2019). Navigating the Shortcomings of Virtual Learning Environments Via Social Media. International Journal of Virtual and Personal Learning Environments (IJVPLE), 9(2), 1-14. https://doi.org/10.4018/IJVPLE.2019070101
 

“From the classroom to Dr. YouTube”: nursing students' experiences of learning and teaching styles in Jordan

Virtual Learning Environment and the Development of Communicative Competences

Assessment of students’ learning styles preferences in the faculty of science, Tishreen University, Syria

A Design Framework for Personal Learning Environments

The problem of this study was to determine whether learning styles of students affect their math achievement scores on the Texas Assessment of Academic Skills Test. The research questions addressed relevant to this study were: 1. Is there a positive correlation between students' learning styles and their achievement test scores in mathematics? 2. Is there a positive correlation between specific sub group's (as deemed by the state of Texas) and gender's learning styles and their achievement test scores in mathematics? The Pearson Product Moment Correlation coefficient and the Point-biserial correlation analysis was applied to the data collected from 500 fifth grade students attending a North Texas Intermediate school. The significance level was established at the .05 level. Part of the data was the student's responses to the Learning Style Inventory by Dunn, Dunn and Price. The findings established that the learning style preferences of all students in the area of persistence significantly impacted their math achievement scores. Gender and ethnicity were mitigating factors in the findings. These learning style preferences significantly impacted achievement in the following ways: * Caucasian students' preference of a high level of persistence in completing a difficult task. * Hispanic students' preference for a warm learning environment and motivational factor of pleasing the teacher. * Afro-American students' preference for kinesthetic learning. * Female students' learning style preferences appear in: - the design of the learning environment - the need for intake of food and/or drink - a high level of responsibility - a high sense of self-motivation , of teacher and of parent motivation. * Male students' learning style preferences appear in: - a warm learning environment - a high level of responsibility - the need for intake of food and/or drink - a high sense of teacher and of parent motivation - a late morning learning In summary, the author suggests that supplying the teachers with information concerning students' learning style preferences will benefit student achievement.

<span>Individuals learn in different ways using several learning styles, but lecturers may not always share material and learning experiences that match students’ learning preferences. Mismatches between learning and teaching styles can lead to disappointment with students are taking, and lead to underperformance among them. The aim of this study is to identify the learning styles of the students enrolled in Universiti Malaysia Pahang who were registered in Programming Technique course and to investigate the relationship between students’ learning styles and teachers’ teaching styles. Five lecturers and 251 students were involved in the study as participants and. Data from students were collected using Leonard, Enid’s VAK Learning Style Survey. Meanwhile, the teaching styles of the lecturers were identified using Grasha and Reichmann’s Teaching Style Survey. The findings revealed that majority of the student’s preferred visual learning style. The result also shows that the lecturers’ teaching styles give an impact towards the <br /> students’ academic performance. From this study, we can conclude that teaching styles have significant impacts on students’ learning styles and academic performances.</span>

Readiness is an important indicator of learners' willingness to engage productively in a virtual learning environment. Low readiness is believed to be the main reason behind virtual learning failure. The purpose of this present study is to investigate the effects of online readiness on learners’ learning satisfaction and performance in a virtual second language learning environment on a sample of 203 Malaysian Non-Arabic Speaking Learners using a cross-sectional survey. This study further explored which dimension of readiness is found to be the strongest predictor of their level of satisfaction and performance. Partial least square structural equation modeling (PLS-SEM) analysis examined the predictive relationships between readiness, satisfaction, and performance. The results proved that online readiness was statistically a significant predictor of their learning satisfaction and performance, indicating computer and internet self-efficacy in performing activities in the virtual learning environment as the strongest predictor. By identifying the most influential predictors, this groundbreaking study recognizes which key elements of the virtual learning environment language learners would need more to relish learning and achieve their goals. This study offers critical insights that have not been previously explored by conducting a comprehensive analysis of the factors influencing learning satisfaction and performance. The findings, therefore, highlight the paramount importance of assessing the readiness of online learners and their learning environment, providing valuable guidance for higher education institutions seeking to enhance the success of VLLE. In addition, this study sets a precedent for future research in the field. It underscores the need for ongoing efforts to improve virtual language learning environments to serve students’ needs better.

This study investigated the effect of rhythm based computer-assisted music instruction designed for individual learning style preferences. Participants were undergraduate preservice elementary education majors (N = 82) enrolled in Fundamentals of Music. The Perceptual Learning Style Preferences Survey and the Diablo Valley College Learning Style Survey were used to measure learning preferences. Two content knowledge assessments were administered as pre and posttest: (a) Music Achievement Test (MAT) Test 2-Part 3-Auditory and Visual Discrimination subtest b and (b) Researcher-Developed Rhythm Test (RDRT). Researcher-developed software programs were constructed, teaching participants the basic elements of rhythm based on learning style preferences. Forty-three of the participants (13 auditory, 13 visual, and 17 tactile/kinesthetic) completed software programs designed for their individual learning preferences. A stratified randomly selected group (11 auditory, 10 visual, and 18 tactile/kinesthetic) was assigned software that addressed all learning style strategies (n = 39) to complete the rhythm unit. A repeated measures multivariate analysis of variance (MANOVA) conducted to determine the effect of three types of learning style strategies and two treatments (learner specific and all learning styles) on the two dependent variables (MAT and RDRT) revealed significant differences between the dependent measures. Two separate three-way repeated measures ANOVAs calculated on the MAT and RDRT found significant differences from pretest to posttest, indicating a significant increase in skill level on both measures. MAT scores revealed no significant differences with regards to treatment or learning style preferences. A significant two-way interaction between treatment and pretest to posttest was found for the RDRT. Both groups made significant gains due to treatment from pretest to posttest. The gain was greater for participants who used all learning styles software than for those who used individualized learning styles software. A significant two-way interaction among learning style strategies, RDRT pretest to posttest, was revealed. All participants made large gains due to treatment; tactile/kinesthetic learners gained noticeably less than aural and visual learners. Participants with the highest and lowest posttest scores (n = 23) from each learning style preference were selected for interviews. Overlapping themes indicated positive acceptance of the program, superior educational value, and creative program design.

This paper discusses the proposed model of the collaborative virtual learning system for the introductory computer programming course which uses one of the collaborative learning techniques known as the “Think-Pair-Share”. The main objective of this study is to design a model for an online learning system that facilitates the collaborative learning activities in a virtual environment such as online communications and pair or small group discussions. In order to model the virtual learning environment, the RUP methodology has been used where it involves the data collection phase and the analysis and design phase. Fifty respondents have been randomly selected to participate in the data collection phase to investigate the students’ interest and learning styles as well as their learning preferences. The results have shown the needs for the development of online small group discussions that can be used as an alternative learning style for programming courses. The proposed design of the virtual learning system named as the Online Collaborative Learning System or OCLS is being depicted using the objectoriented models which are the use-case model and class diagram in order to show the concise processes of virtual “Think-Pair-Share” collaborative activities. The “Think-PairShare” collaborative learning technique that is being used in this model has been chosen because of its simplicity and relatively low-risk. This paper also presents the proposed model of the system’s architecture that will become the guidelines for the physical development of OCLS using the web-based applications.