Applying web-mediated co-curricular learning and phenomenon-based learning to improve students’ programming skills and self-efficacy in an online programming course

Universal Access in the Information Society - Aiming to develop practical programming skills and self-efficacy of students in an online learning environment, two teaching approaches were integrated...     

Developing early warning systems to predict students’ online learning performance

An early warning system can help to identify at-risk students, or predict student learning performance by analyzing learning portfolios recorded in a learning management system (LMS). Although previous studies have shown the applicability of determining learner behaviors from an LMS, most investigated datasets are not assembled from online learning courses or from whole learning activities undertaken on courses that can be analyzed to evaluate students’ academic achievement. Previous studies generally focus on the construction of predictors for learner performance evaluation after a course has ended, and neglect the practical value of an “early warning” system to predict at-risk students while a course is in progress. We collected the complete learning activities of an online undergraduate course and applied data-mining techniques to develop an early warning system. Our results showed that, time-dependent variables extracted from LMS are critical factors for online learning. After students have used an LMS for a period of time, our early warning system effectively characterizes their current learning performance. Data-mining techniques are useful in the construction of early warning systems; based on our experimental results, classification and regression tree (CART), supplemented by AdaBoost is the best classifier for the evaluation of learning performance investigated by this study.     

Effect of AR-based online wearable guides on university students’ situational interest and learning performance

Universal Access in the Information Society - This study addresses whether augmented reality (AR)-based online wearable guides are better at improving learners’ situational interest (with...     

Advancing students’ computational thinking skills through educational robotics: A study on age and gender relevant differences

This work investigates the development of students’ computational thinking (CT) skills in the context of educational robotics (ER) learning activity. The study employs an appropriate CT model for operationalising and exploring students’ CT skills development in two different age groups (15 and 18 years old) and across gender. 164 students of different education levels (Junior high: 89; High vocational: 75) engaged in ER learning activities (2 hours per week, 11 weeks totally) and their CT skills were evaluated at different phases during the activity, using different modality (written and oral) assessment tools. The results suggest that: (a) students reach eventually the same level of CT skills development independent of their age and gender, (b) CT skills in most cases need time to fully develop (students’ scores improve significantly towards the end of the activity), (c) age and gender relevant differences appear when analysing students’ score in the various specific dimensions of the CT skills model, (d) the modality of the skill assessment instrument may have an impact on students’ performance, (e) girls appear in many situations to need more training time to reach the same skill level compared to boys.     

Pre-service teachers’ skills and perceptions about the use of virtual learning environments to improve teaching and learning

This paper explores data retrieved from Educational Immersive Virtual Worlds to describe pre-service teachers’ skills and perceptions about the simulation tasks. This project had 10 participants who were immersed for 3 years in the Technology and Pedagogical Models in Immersive Worlds island, a multi-user virtual environment in Second Life and Open Simulator. In this project, we evaluated how three-dimensional virtual environments can facilitate the achievement of teaching and learning processes. Based on quantitative and qualitative methodologies, two data collection instruments were applied. Through observation grids and personal log books, professional performance of the 18 pedagogical challenges implemented was collected. The statistical analysis shows that the students improved their technology skills and educational aspects about good practices in classes, regardless of the type of platform used. The analysis through Constant Comparing Method reported a positive assessment of the use of virtual environments, especially about the use of teaching strategies. Main conclusions regarding the pedagogical context reflect the importance of peer assessment on teaching performance, as well as the complexity of role-plays as intellectual challenges to enhance pre-service teachers’ skills. The main difficulties identified during the development of the activities were technical in nature, reporting hardware and connectivity issues.     

An online game approach for improving students’ learning performance in web-based problem-solving activities

In this paper, an online game was developed in the form of a competitive board game for conducting web-based problem-solving activities. The participants of the game determined their move by throwing a dice. Each location of the game board corresponds to a gaming task, which could be a web-based information-searching question or a mini-game; the former was used to guide the participants to search for information to answer a series of questions related to the target learning issue, while the latter was used to provide supplementary materials during the gaming process. To evaluate the performance of the proposed approach, an experiment was conducted on an elementary school natural science course. The experimental results showed that the proposed approach not only significantly promoted the flow experience, learning attitudes, learning interest and technology acceptance degree of the students, but also improved their learning achievements in the web-based problem-solving activity.     

Enhancing students’ knowledge building through utilising social interactions in an online learning environment

ABSTRACT

In the new “open world” of information, educational systems should involve students in constructing new knowledge of value to a community out of fragmentary information. The already proposed Knowledge Building (KB) approaches typically support only a few general-purpose activities due to the constraints of the utilised web-based environments. To organise and facilitate students’ KB during course activities, this study incorporated services provided by DoosMooc social learning environment into a knowledge transformation model. This approach is completely adapted to an educational context and allows time for iterations, helping students to both contribute to social KB processes and take collective responsibility for improving their understanding of authentic problems. The features provided by the introduced environment support and assess students’ KB activities and facilitate processes of creating, representing, organising, and reviewing different types of knowledge artefacts. The results of a semester-long experiment indicate that the approach and the corresponding instructional design thereof could successfully organise students’ KB activities and facilitate the required interactions. This study reports the impacts of parameters such as learner expertise and quality of shared knowledge on the planned KB processes, and investigates the relationships between students' KB activities and learning achievements.     

What do students do on-line? Modeling students' interactions to improve their learning experience

In this work, we present an approach to model and analyze students interactions, within a gamified on-line learning environment, in order to assist teachers and tutors (education professionals) decision-making, regarding their students learning experience. We noticed that asking students this information might not bring precise and dynamic results for all students. This way, we characterize the educational resources available in the studied environment, and collected data from students interactions with these resources. Our objective was to generate the students’ interactional profile (a model of their interactions). The information, then, is presented to teachers and tutors, who should use it to guide their pedagogical decision-making process. In this study, the types of interactions were used to personalize gamification elements named missions. We experimented the approach with two groups of users from the studied environment (MeuTutor). The data analysis showed differences in the way these groups were performing, where group B was considerably above group A. We sent the personalized missions (following our approach) to every student from group A, and waited some time for them to interact with it. In the end we checked the effect of this treatment, which, according to the results, promoted relevant improvement in group A interactions.     

If online learning works for you,what about deaf students? Emerging challenges of online learning for deaf and hearing-impaired students during COVID-19: a literature review

Universal Access in the Information Society - With the coronavirus (COVID-19) outbreak, educational systems worldwide were abruptly affected and hampered, causing nearly total suspension of all...     

Benefit factors: American students,International students,and deaf/hard of hearing students’ willingness to pay for captioned online courses

To recognize captioning benefits as a part of Universal Design, the study proposed to identify captioning benefits of American students who are native speakers, American students who are English as second language learners, International students, and deaf and hard of hearing students from two California universities. This study used the contingent valuation method, specifically, willingness to pay for survey design. Imagining if a university offers a captioned online course, the four groups were asked what factors they would be willing to pay for captioned online courses. American students and International students would be willing to pay for a variety of reasons, such as academic achievement, environmental convenience, and accessibility. Captioning benefits were not limited to deaf and hard of hearing students for accommodations, but also to American students and International students. The results could be a possibility of expanding future captioned online courses at universities as part of a Universal Design curriculum.     

Usability of a cloud-based collaborative learning framework to improve learners’ experience

Computer-Supported Collaborative Learning (CSCL) is concerned with how Information and Communication Technology (ICT) might facilitate learning in groups which can be co-located or distributed over a network of computers such as Internet. CSCL supports effective learning by means of communication of ideas and information among learners, collaborative access of essential documents, and feedback from instructors and peers on learning activities. As the cloud technologies are increasingly becoming popular and collaborative learning is evolving, new directions for development of collaborative learning tools deployed on cloud are proposed. Development of such learning tools requires access to substantial data stored in the cloud. Ensuring efficient access to such data is hindered by the high latencies of wide-area networks underlying the cloud infrastructures. To improve learners’ experience by accelerating data access, important files can be replicated so a group of learners can access data from nearby locations. Since a cloud environment is highly dynamic, resource availability, network latency, and learner requests may change. In this paper, we present the advantages of collaborative learning and focus on the importance of data replication in the design of such a dynamic cloud-based system that a collaborative learning portal uses. To this end, we introduce a highly distributed replication technique that determines optimal data locations to improve access performance by minimizing replication overhead (access and update). The problem is formulated using dynamic programming. Experimental results demonstrate the usefulness of the proposed collaborative learning system used by institutions in geographically distributed locations.     

Identify predictors of university students’ continuance intention to use online carbon footprint calculator

An online carbon footprint calculator (CFC) is a Green Information System, which enables individuals to self-estimate carbon footprints, self-manage behaviour, and accordingly self-control carbon emissions. Individuals’ persistent CFC use may help to slow down global warming. Thus, it is vital to establish a model to investigate the motivational predictors of CFC continuance intention. We formulated a model by integrating Expectation-Confirmation Model (ECM) and Theory of Planned Behaviour (TPB), with the former measuring continuance intention and the latter measuring low-carbon behavioural intention. To validate the model and identify significant predictors, a survey was conducted on undergraduate students. The survey results revealed that ECM accounted for 50% of the variance in continuance intention, that TPB accounted for 35% in low-carbon behavioural intention, and that the integrated model accounted for 64% in CFC continuance intention. Plus, direct and significant predictors of CFC continuance intention included low-carbon attitude, low-carbon behavioural intention, low-carbon subjective norm, satisfaction, and usefulness. Findings, implications, and suggestions are accordingly offered.     

Do students need teacher’s initiation in online collaborative learning?

As more and more people use computers to complete their work and solve problems in the workplace, computing education is emphasized for students of all levels and disciplines in Taiwan. However, the computing education in Taiwan can hardly be recognized as effective and satisfactory. Many inappropriate examples that lack context are used in teaching and textbooks that may result in employees with low competence and insufficient ability for collaborative working. Students who grow up in this learning context usually lack the ability to seek information and solve problems by themselves. In this regard, the author redesigned a course and adopted online collaborative learning with initiation to establish the essential knowledge for students’ collaboration in the initial stage of a course. This study conducted an experiment that included 169 undergraduates from three class sections – the first two from an academic university (Case 1, n = 68; Case 2, n = 68) and the last one from a university of science and technology (Case 3, n = 33) – taught by the same teacher under the same course name and the same course website. The results show that students who received online collaborative learning with initiation had higher grades than those without. The author further discusses the implications for teachers, schools, and scholars who plan to provide online courses for their students, particularly computing courses.     

Mining students’ behavior in web-based learning programs

There has been a proliferation of web-based learning programs (WBLPs). Unlike traditional computer-based learning programs, WBLPs are used by a population of learners who have diverse background. How different learners access the WBLPs has been investigated by several studies, which indicate that cognitive style is an important factor that influences learners’ preferences. However, these studies mainly use statistical methods to analyze learners’ preferences. In this paper, we propose to analyze learners’ preferences with a data mining technique. Findings in our study show that Field Independent learners frequently use backward/forward buttons and spent less time for navigation. On the other hand, Field Dependent learners often use main menu and have more repeated visiting. Implications for these findings are discussed.     

Book2U and students’ learning styles: the effect of learning styles on intention to use a social media-enabled tool

Universal Access in the Information Society - This study investigated the factors that affect the intention to use social media for learning among students from the higher learning institutions. A...     

Intercultural Talent Management Model: Virtual communities to promote collaborative learning in indigenous contexts. Teachers’ and students’ perceptions

The strong connection between technologies and globalization has made the phenomenon of interculturality increase at a global level. The aim was to determine the perception of teachers and students in the use of a Model of Talent Management for interculturality. A virtual learning environment (VLE) was used to link teachers and students of 5 schools in disadvantaged context of Chile through collaborative learning. The research is interpretive and positivist based on qualitative method approach, with quantitative contributions. Results show that talents of the students contribute to the formation of cultural identity that gives uniqueness to the human group to which they belong and the perception of teachers is that the phenomena of acculturation, enculturation and transculturation processes occur in learning linked to the management of the talents of students in intercultural contexts. With respect to the proposed model, trends indicate that it is possible to diagnose and promote talent through collaborative learning and intercultural dialogue. As for technology, it could be argued that it has reshaped relations between different cultures.     

Enhancing students’ botanical learning by using augmented reality

Universal Access in the Information Society - Scientific literacy is considered a crucial part of learners’ basic capacities. In primary schools, scientific literacy is generally cultivated...     

Predicting students’ learning style using learning analytics: a case study of business management students from India

ABSTRACT

Business Management Education in India has shown an upward growth trend in the last couple of decades. Due to the diverse nature of the course, students from diverse academic backgrounds are being admitted to the course. Therefore, differences in students’ abilities and their learning styles have a significant effect on their learning outcomes. Meanwhile, with the development of learning technologies, learners can be provided a more effective learning environment to optimise their learning. The purpose of this study was to develop a model to automatically detect the students’ learning styles from their personal, academic and social media data and make recommendations for students, teachers, educators and administrators for overall improvement of learning outcomes. Data analysis in this research was represented using data collected from post-graduate business management students in India. A 10-fold cross-validation was used to create and test the models. The data were analysed by R and R-Studio. Classification accuracy, Precision, Recall, Kappa, ROC curve and F measure were observed. The results showed that the accuracy of classification by the C4.5 technique had the highest value at 95.7%, and it could be applied to develop Felder–Silverman’s learning style while taking into consideration students’ academic, personal information and social media preferences.