Unifying heterogeneous e-learning modalities in a single platform: CADI, a case study

Current e-learning forms are commonly based on improving the learning process through the enhancement of certain skills in students, such as collaborative, competitive or problem-based learning. However, it seems that there is still no e-learning formula that gathers the implementation of a number of more generic educational principles in a single e-learning system or platform. Therefore, this paper presents a web-based framework for the creation, development and implementation of heterogeneous learning environments called CADI. It offers a graphical user interface for students to interact with only the need for any generic WiFi compliant device. Its innovative design allows the instructor to select and combine the developed resources to create varied activities, providing content adapted to every single device. The usefulness of the system was tested by introducing a case study to a group of senior college students. The experience showed that the use of the system helped students to achieve better results in their evaluation. It also showed that the students had no problems interacting with it from the outset, promoting their active learning. Design, implementation and assessment results of the system are also presented and analyzed.     

The influence of collaboration styles to children’s cognitive performance in digital problem-solving game “William Adventure”: A comparative case study

Since a large variety of digital games have been used in many fields for educational purposes, their real functions in learning have caught much attention as well. This study first defines learning characteristics of problem-solving digital games and their corresponding cognitive levels, then designs and develops a problem-solving game in accordance to the criteria. Tasks in the game context are inter-related to each other so that players need to critically and creatively think about problem solutions. Learners’ task analyses are performed to observe four elementary learners’ gaming paths, behaviors and cognitive activities, individually and collaboratively. System documentation, video recording, researcher observation, and interviews are conducted to analyze learners’ learning strategies and their cognitive performance during the gaming process.     

An investigation of learners' collaborative knowledge construction performances and behavior patterns in an augmented reality simulation system

The purpose of this study was to investigate how a mobile collaborative augmented reality (AR) simulation system affects learners' knowledge construction behaviors and learning performances. In this study, 40 undergraduate students were recruited and divided into dyads to discuss a given task either with the assistance of a mobile collaborative AR system or traditional 2D simulation system. The participants' knowledge acquisition regarding elastic collision was evaluated through a pre-test and a post-test comparison. Learners' knowledge construction behaviors were qualitatively identified according to an adapted three-category coding scheme including construction of problem space (PS), construction of conceptual space (CS), and construction of relations between conceptual and problem space (CPS), and were then analyzed by adopting lag sequential analysis. The results indicated that the learners who learned with the AR system showed significant better learning achievements than those who learned with the traditional 2D simulation system. Furthermore, the sequential patterns of the learners' behaviors were identified, including three sustained loops (PS→PS, CS→CS, CPS→CPS), a bi-directional path between the PS and CPS activities (PS↔CPS), and a one way path from the PS activity to the CS activity (PS→CS). The revealed behavior patterns suggest that the AR Physics system may serve as a supportive tool and enable dyad learners to respond quickly to the displayed results and support their knowledge construction processes to produce a positive outcome. Based on the behavioral patterns found in this study, suggestions for future studies and further modifications to the system are proposed.     

Cross-age peer tutors in asynchronous discussion groups: Exploring the impact of three types of tutor training on patterns in tutor support and on tutor characteristics

This study was conducted in an authentic university setting with fourth-year Educational Sciences’ students operating as online peer tutors to facilitate freshman tutees’ online collaboration and knowledge construction in a blended “Instructional Sciences” course. Taking into account prior research uncovering weaknesses in online peer tutor behaviour, the aim of the study was to explore the possibility to optimise the quality and the nature of online peer support. In this respect, the study examined the impact of three tutor training conditions (multidimensional support, model/coach, and control condition) on peer tutors’ actual tutor behaviour in asynchronous discussion groups and on tutors’ self-efficacy beliefs, perceived collective efficacy, and training evaluation. Quantitative content analysis was applied to study online peer tutor behaviour. More specifically, two coding schemes were used focusing respectively on the occurrence of different e-moderating activities and on the evolution from modeling to coaching behaviour. Tutors’ self-efficacy beliefs, perceived collective efficacy, and training evaluation were assessed by means of questionnaires.     

Psychological safety and social support in groupware adoption: A multi-level assessment in education

In this paper, the authors propose that psychological safety, a sense of interpersonal trust and being valued in a work team, is an important determinant of groupware technology adoption in an educational setting. They develop and test a model of antecedents and consequences of psychological safety. Data were collected from 361 university students, organized in 36 teams. Results of multi-level regression analysis reveal positive individual-level effects of perceived tutor support and perceived peer support on psychological safety. Furthermore, our findings show a positive unique group-level effect of perceived tutor support on psychological safety, where an individual’s level of self-consciousness strengthens this positive impact. In addition, findings of structural equation modeling demonstrate that both perceived usefulness and perceived ease of use partially mediate the positive effect of psychological safety on groupware usage. Psychological safety also shows a positive direct effect on groupware usage. Finally, a student’s offline communication frequency with his tutor and peers appears to strengthen the impact of psychological safety on perceived usefulness, perceived ease of use, and groupware usage.     

Automatic detection of learning styles for an e-learning system

A desirable characteristic for an e-learning system is to provide the learner the most appropriate information based on his requirements and preferences. This can be achieved by capturing and utilizing the learner model. Learner models can be extracted based on personality factors like learning styles, behavioral factors like user’s browsing history and knowledge factors like user’s prior knowledge. In this paper, we address the problem of extracting the learner model based on Felder–Silverman learning style model. The target learners in this problem are the ones studying basic science. Using NBTree classification algorithm in conjunction with Binary Relevance classifier, the learners are classified based on their interests. Then, learners’ learning styles are detected using these classification results. Experimental results are also conducted to evaluate the performance of the proposed automated learner modeling approach. The results show that the match ratio between the obtained learner’s learning style using the proposed learner model and those obtained by the questionnaires traditionally used for learning style assessment is consistent for most of the dimensions of Felder–Silverman learning style.     

A quantitative multimodal discourse analysis of teaching and learning in a web-conferencing environment – The efficacy of student-centred learning designs

This paper presents a quantitative approach to multimodal discourse analysis for analyzing online collaborative learning. The coding framework draws together the fields of systemic functional linguistics and Activity Theory to analyze interactions between collaborative-, content- and technology-related discourse. The approach is used to examine how the task subject matter, the activity design, and the choice of interface affected interaction and collaboration for a computing course conducted in a web-conferencing environment. The analysis revealed the critical impact of activity design on the amount and type of discourse that transpired. Student-centred designs resulted in over six times more student discourse as compared to teacher-centred designs and created a learning environment where students took greater ownership over the tasks and contributed more to the content-based discussion. The paper also incorporates a rationale for the approach to coding and a reflection on its efficacy for discourse analysis in technology-based learning environments.     

Virtual reality for collaborative e-learning

In the past, the term e-learning referred to any method of learning that used electronic delivery methods. With the advent of the Internet however, e-learning has evolved and the term is now most commonly used to refer to online courses. A multitude of systems are now available to manage and deliver learning content online. While these have proved popular, they are often single-user learning environments which provide little in the way of interaction or stimulation for the student. As the concept of lifelong learning now becomes a reality and thus more and more people are partaking in online courses, researchers are constantly exploring innovative techniques to motivate online students and enhance the e-learning experience. This article presents our research in this area and the resulting development of CLEV-R, a Collaborative Learning Environment with Virtual Reality. This web-based system uses Virtual Reality (VR) and multimedia and provides communication tools to support collaboration among students. In this article, we describe the features of CLEV-R, its adaptation for mobile devices and present the findings from an initial evaluation.     

The nature, reception, and use of online peer feedback in higher education

This article focuses on the use of online interactive peer feedback in higher education and identifies the successful uptake of feedback as an important aspect. We investigate the link between the nature of students’ feedback, the way it is evaluated by the receiver, and its consecutive use for the revision of students’ products. Two separate studies were conducted to investigate the link between these three variables across different educational contexts and tools. Both studies showed a significant relationship between feedback containing concrete suggestions and a successful uptake of the feedback. Regarding the different tools that were used, these concrete suggestions were more often produced in the Annotation system than in the Blackboard discussion forum, the latter showing more evaluative forms of feedback. We also found significant relationships between elements of both the nature and the reception of feedback on the one hand, and the use of this feedback by the receiver on the other hand.     

Enhancing skill in constructing scientific explanations using a structured argumentation scaffold in scientific inquiry

Constructing scientific explanations is necessary for students to engage in scientific inquiry. The purpose of this study is to investigate the influence of using a structured argumentation scaffold to enhance skill in constructing scientific explanations in the process of scientific inquiry. The proposed approach is designed to scaffold the following aspects of argumentation: the argumentation process, the explanation structuring, explanation construction, and explanation evaluation. A quasi-experiment was conducted to examine the effectiveness of the structured argumentation scaffold in developing skill in constructing scientific explanations and engaging in electronic dialogues. A web-based collaborative synchronous inquiry system, ASIS (Argumentative Scientific Inquiry System), was utilized to support students as they worked in groups to carry out inquiry tasks. Two intact sixth grade classes (n = 50) participated in the study. The data show that the ASIS with the structured argumentation scaffold helped students significantly improve their skills in constructing scientific explanations, make more dialogue moves for explanation and query, and use more of all four argument components. In addition, the use of warrants, one of the components of an argument, was found to be a critical variable in predicting students' competence with regard to constructing scientific explanations. The results provide references for further research and system development with regard to facilitating students' construction of scientific argumentation and explanations.     

Supporting teachers in guiding collaborating students: Effects of learning analytics in CSCL

The aim of this study was to examine the effects of teacher supporting tools that present summaries, visualizations, and analyses of student participation and discussion on the way teachers guide collaborating groups of students in a digital learning environment. An experimental set-up was used in which authentic student data was converted to simulation vignettes that participants could interact with, enabling them to act as the teacher. The vignettes contained groups that had a problem concerning participation or discussion. When presented with the supporting tools, teachers and student teachers were better able to spot the problems regarding participation, intervened more often in problematic groups as time progressed, and displayed more specific explanations of their actions.     

Group differences in computer supported collaborative learning: Evidence from patterns of Taiwanese students’ online communication

This study explored the differences among online elementary school student groups based on their communication features. Two hundred and ninety-one Taiwanese students, ranging in age from 11 to 12 years old, participated in this study. The students were randomly arranged within-class into three-member groups. Each group was asked to use a collaborative learning system to accomplish a group task generating a shared concept map. The textual discussions in each group during collaboration were collected, coded, categorized, and quantified to profile their communication characteristics. Cluster analysis on the resulting communication characteristics resulted in four types of small student groups, including passive or reticent, frequently off-task, actively participating, and knowledge emphasizing. Most student groups (56%) were found to be relatively passive or reticent. Frequently off-task student groups made a protrusive amount of messages for off-task social purposes. The actively participating student groups were characterized by abundant discussion, particularly for continuing task, managing procedure and coordinating efforts. The distinctive feature of knowledge emphasizing student groups was that they devoted particular attention to task related knowledge. In addition, they performed better in task accomplishment.     

Learning in asynchronous discussion groups: a multilevel approach to study the influence of student, group and task characteristics

The research reported in the current article studies the impact of learning in asynchronous discussion groups on students' final exam scores and levels of knowledge construction. Multilevel analyses were applied to uncover the specific influence of student, group and task variables. The results indicate that the impact of student characteristics on both dependent variables is of higher significance than characteristics of the discussion group students are allocated to. With regard to levels of knowledge construction, task characteristics also appear to be of importance.

 With regard to final exam scores the analyses reveal a significant impact from student learning style, attitude towards task-based learning, the number of student contributions and the level of knowledge construction in these contributions. No significant group characteristics were observed.

 As to levels of knowledge construction, the analyses revealed that the amount of contributions and the attitude towards the online learning environment are significant predictors. The intensity of the interaction in a group had a significant impact. As to task characteristics, significant differences were found between consecutive themes. These disappeared when taking into account task complexity.     

Designing,visualizing, and discussing algorithms within a CS 1 studio experience: An empirical study

Within the context of an introductory CS1 unit on algorithmic problem-solving, we are exploring the pedagogical value of a novel active learning activity—the “studio experience”—that actively engages learners with algorithm visualization technology. In a studio experience, student pairs are tasked with (a) developing a solution to an algorithm design problem, (b) constructing an accompanying visualization with a storyline, and finally (c) presenting that visualization for feedback and discussion in a session modeled after an architectural “design crit.” Is a studio experience educationally valuable? What kind of technology can best support it? To explore these questions, we conducted an empirical study of two alternative CS1 studio experiences in which students used one of two different kinds of algorithm development and visualization technology: (a) a text editor coupled with art supplies, or (b) ALVIS Live!, a computer-based algorithm development and visualization tool. We found that the students who used ALVIS Live! developed algorithms with significantly fewer semantic errors. Moreover, discussions mediated by ALVIS Live! had significantly more student audience contributions, and retained a sharper focus on the specific details of algorithm behavior, leading to the collaborative identification and repair of semantic errors. In addition, discussions mediated by both ALVIS Live! and art supplies contained substantial evidence of higher order thinking. Based on our results, we make recommendations for educators interested in exploring studio-based approaches, and we propose an agenda for future research into studio-based learning in computer science education.     

A study of social participation and knowledge sharing in the teachers' online professional community of practice

To facilitate professional development of teachers in the online context, the online community of practice (CoPs) has become an important platform in which individuals with similar interests or common goals get together to share their resources, develop working strategies, solve problems, and improve individual as well as organizational performance. In this study, we have collected self-reported knowledge-sharing behaviors from 321 members of the largest online professional CoP of teachers in Taiwan. The results show that closer connections among online CoP members can lead to greater recognition of and altruism towards others. Moreover, performance expectation and self-efficacy belief play essential roles in knowledge-sharing participation. Thus, the development of social relationships among online teacher members helps them obtain potential resources and reliable support through their social network. Also, teachers' membership in the online professional CoP fosters a prosocial attitude that heightens their willingness to share useful resources and solve other members' problems, both emotionally and instrumentally. Consequently, knowledge-sharing behaviors, in terms of knowledge giving and knowing receiving, are significantly predicted by prosocial commitment and performance expectation respectively. The implications to both research and practice are provided in this paper.     

Differences in learning processes between successful and less successful students in computer-supported collaborative learning in the field of human nutrition and health

This study aimed to investigate the differences in learning processes between successful and less successful pairs of students in computer-supported collaborative learning (CSCL) in the field of human nutrition and health. As part of their regular MSc (and optional BSc) course “Exposure assessment in nutrition and health research” at Wageningen University, 44 students were asked (as an individual pretest) to design and analyze a study which evaluates a certain dietary assessment method. Subsequently, they were asked to discuss their evaluation studies in randomized pairs using a CSCL platform. As an individual posttest, students had to re-design and re-analyze the same evaluation study. The quality of students’ knowledge construction in both tests and characteristics of their learning processes in the CSCL environment were assessed through two coding schemes. Based on their learning outcomes (quality of knowledge construction), pairs of students were divided into two subgroups: successful and less successful students. Next, the learning processes of these subgroups were compared. This study revealed that the learning processes of successful and less successful students in the CSCL environment differed in terms of relevance, width and depth of discussion and justification and reasoning. Based on these findings, recommendations for further research and educational practice are formulated.     

The influences of a two-tier test strategy on student learning: A lag sequential analysis approach

Recently, programming skills have become a core competence. Many teaching strategies were developed to improve programming skills. Among them, online tests were widely applied to enhance students learning. Nonetheless, they may not be able to engage students in deep thinking and reflections. Thus, a two-tier test strategy was proposed to address this issue. However, previous research mainly focused on investigating the effectiveness of the two-tier test strategy but there is a lack of studies that investigate why the two-tier test approach is effective. To this end, we developed an online test, where the two-tier test strategy was implemented. Additionally, an empirical study was conducted to explore the influences of the two-tier test approach on students' learning performance and behavior patterns. Pre-test and post-test scores were applied to assess students' learning performance while a lag sequential analysis was used to analyze behavior patterns. Regarding learning performance, the proposed two-tier test can improve students' programming skills. Regarding behavior patterns, the two-tier test approach facilitates students to develop a learning by reviewing strategy, which is useful to improve their programming skills.     

The comparisons of the influences of prior knowledge on two game-based learning systems

Game-based learning provides many benefits, such as enhancing the interaction with students and stimulating their learning motivation. Thus, it is popular to learners who have diverse characteristics. To this end, individual differences play an essential role. Among various individual differences, previous studies demonstrated that prior knowledge has great effects on game-based learning. However, such studies mainly considered a single game-based learning system. To address this issue, this study examined how prior knowledge affects students' reactions to two different types of game based learning systems, i.e., the Machinarium and the CSI: Web Adventures. The former delivers procedural knowledge while the latter provides declarative knowledge. The results from this study indicate that prior knowledge has positive impacts in the CSI group while it has negative impacts in the Machinarium group. These findings imply that prior knowledge is useful for the context of declarative knowledge while it may not be helpful for the context of procedural knowledge.     

Learning motivation in e-learning facilitated computer programming courses

Computer programming skills constitute one of the core competencies that graduates from many disciplines, such as engineering and computer science, are expected to possess. Developing good programming skills typically requires students to do a lot of practice, which cannot sustain unless they are adequately motivated. This paper reports a preliminary study that investigates the key motivating factors affecting learning among university undergraduate students taking computer programming courses. These courses are supported by an e-learning system – Programming Assignment aSsessment System (PASS), which aims at providing an infrastructure and facilitation to students learning computer programming. A research model is adopted linking various motivating factors, self-efficacy, as well as the effect due to the e-learning system. Some factors are found to be notably more motivating, namely, ‘individual attitude and expectation’, ‘clear direction’, and ‘reward and recognition’. The results also suggest that a well facilitated e-learning setting can enhance learning motivation and self-efficacy.