Can we predict success from log data in VLEs? Classification of interactions for learning analytics and their relation with performance in VLE-supported F2F and online learning

Learning analytics is the analysis of electronic learning data which allows teachers, course designers and administrators of virtual learning environments to search for unobserved patterns and underlying information in learning processes. The main aim of learning analytics is to improve learning outcomes and the overall learning process in electronic learning virtual classrooms and computer-supported education. The most basic unit of learning data in virtual learning environments for learning analytics is the interaction, but there is no consensus yet on which interactions are relevant for effective learning. Drawing upon extant literature, this research defines three system-independent classifications of interactions and evaluates the relation of their components with academic performance across two different learning modalities: virtual learning environment (VLE) supported face-to-face (F2F) and online learning. In order to do so, we performed an empirical study with data from six online and two VLE-supported F2F courses. Data extraction and analysis required the development of an ad hoc tool based on the proposed interaction classification. The main finding from this research is that, for each classification, there is a relation between some type of interactions and academic performance in online courses, whereas this relation is non-significant in the case of VLE-supported F2F courses. Implications for theory and practice are discussed next.     

Artificial intelligence in education: an exploration

The research field of Artificial Intelligence in Education (AIED) embraces a wide diversity of research interests. Psychology, education and cognitive science are strongly represented, alongside computer science and artificial intelligence. A key interest is in modelling, especially of learning processes and cognition. This paper gives a brief outline of the development of AIED, and examples of current issues and projects. The 'AI' in the title may give a misleading picture of a research field that is in fact dynamic and broad, with many links to the classroom.     

The role of academic motivation in Computer-Supported Collaborative Learning

In recent years, increasing attention has been devoted to virtual learning. In the last decade, a large number of studies in Computer-Supported Collaborative Learning (CSCL) have assessed how social interaction, learning processes and outcomes in virtual settings are intertwined. Although recent research findings indicate that learners differ with respect to the amount and type of discourse contributed in virtual settings, little is known about the causes of these differences. The research presented here looks into the effects of motivation of learners on their contribution to discourse using the Deci and Ryan framework of (intrinsic/extrinsic) motivation.This study of 100 participants who were randomly distributed in six groups of 14 members collaborated in a virtual setting to remediate deficiencies in economics indicates that individuals differed with respect to the amount of discourse activity. Furthermore, an integrated multi-method approach (Content Analysis, Social Network Analysis and Academic Motivation Scale) was used in order to examine the impact of academic motivation on the type of discourse activity contributed and on the position of the learner in the social network. The results indicate that highly intrinsically motivated learners become central and prominent contributors to cognitive discourse. In contrast, extrinsically motivated learners contribute on average and are positioned throughout the social network. The research results reveal that differences in academic motivation influences the type of contributions to discourse as well as the position a learner takes within the social network.     

The effects of time-compressed audio and verbal redundancy on learner performance and satisfaction

Digital audio is becoming increasingly popular in higher education with faculty digitally recording and broadcasting lectures for students to learn-on-demand. Students have discovered accelerated playback features in popular computer software and use it to reduce the amount of time spent listening to audio-enhanced instruction. In the current study, 183 undergraduates were randomly assigned to one of three audio-enhanced multimedia presentations that were recorded at three speeds (1.0, 1.4, and 1.8). Results show no significant difference on performance across treatments and a significant difference on satisfaction in favor of 1.4 times the normal audio speed. The results also indicate statistical differences in favor of verbal redundancy, in which the same verbal information was presented on both an auditory and visual channel.     

Transfer of learning in virtual environments: a new challenge?

The aim of all education is to apply what we learn in different contexts and to recognise and extend this learning to new situations. Virtual learning environments can be used to build skills. Recent research in cognitive psychology and education has shown that acquisitions are linked to the initial context. This provides a challenge for virtual reality in education or training. A brief overview of transfer issues highlights five main ideas: (1) the type of transfer enables the virtual environment (VE) to be classified according to what is learned; (2) the transfer process can create conditions within the VE to facilitate transfer of learning; (3) specific features of VR must match and comply with transfer of learning; (4) transfer can be used to assess a VE’s effectiveness; and (5) future research on transfer of learning must examine the singular context of learning. This paper discusses how new perspectives in cognitive psychology influence and promote transfer of learning through the use of VEs.     

A model of (en)action to approach embodiment: a cornerstone for the design of virtual environments for learning

This paper presents a model of (en)action from a conceptual and theoretical point of view. This model is used to provide solid bases to overcome the complexity of designing virtual environments for learning (VEL). It provides a common grounding for trans-disciplinary collaborations where embodiment can be perceived as the cornerstone of the project. Where virtual environments are concerned, both computer scientists and educationalists have to deal with the learner/user’s body; therefore the model provides tools with which to approach both human actions and learning processes within a threefold model. It is mainly based on neuroscientific research, including enaction and the neurophysiology of action.     

Pedagogical-research designs to capture the symbiotic nature of professional knowledge and learning about e-learning in initial teacher education in the UK

This paper argues that if new communications technologies and online spaces are to yield ‘new relationship[s] with learners’ (DfES, 2005, p. 11) then research that is tuned to recognize, capture and explain the pedagogical processes at the centre of such interactions is vital. This has implications for the design of pedagogical activities within Initial Teacher Education (ITE) intended to develop student teachers’ professional knowledge and understanding of e-learning strategies.     

Learning with hypermedia: The influence of representational formats and different levels of learner control on performance and learning behavior

In this paper, two experiments on the use of hypermedia environments for learning about probability theory are reported. In Experiment 1a it was tested whether multimedia design principles (multimedia principle, modality principle, redundancy principle) are valid in hypermedia environments, despite the fact that hypermedia offers more learner control than multimedia. The results showed only little evidence for this validity, although the hypermedia environment entailed only a rather low level of learner control. In Experiment 1b it was investigated how learner control affects performance and how its possible impact is moderated by learners’ prior knowledge. A high level of learner control positively affected the effectiveness of instruction only with regard to intuitive knowledge, but was at the same time accompanied by large increases in learning time, thereby rendering the instruction inefficient. Unexpectedly, effects of learner control were not moderated by students’ prior knowledge. The results imply that the idea to use multimedia design principles for hypermedia learning is too simple and that the benefits and drawbacks of learner control depend heavily on learning objectives and time constraints.     

The contribution of learner characteristics in the development of computer-based adaptive learning environments

The development of learner models takes an active part in upcoming adaptive learning environments. The purpose of learner models is to drive personalization based on learner and learning characteristics that are considered as important for the learning process, such as cognitive, affective and behavioral variables. Despite the huge amount of theoretical propositions of learner characteristics considered as relevant for learner models, practical payoffs are rather sparse. This study aims to overview the empirical research on the mere value of learner models in the development of adaptive learning environments. The results show that a lot of high-quality studies are situated in a rather shattered research field, building few bridges from theory to practice. We conclude with the call for a theory or framework integrating current and past research results that is able to guide theory-based and systematic empirical research having concrete hypotheses on the merits of learner characteristics in adaptive learning environments.     

Monitoring student progress using virtual appliances: A case study

The interactions that students have with each other, with the instructors, and with educational resources are valuable indicators of the effectiveness of a learning experience. The increasing use of information and communication technology allows these interactions to be recorded so that analytic or mining techniques are used to gain a deeper understanding of the learning process and propose improvements. But with the increasing variety of tools being used, monitoring student progress is becoming a challenge. The paper answers two questions. The first one is how feasible is to monitor the learning activities occurring in a student personal workspace. The second is how to use the recorded data for the prediction of student achievement in a course. To address these research questions, the paper presents the use of virtual appliances, a fully functional computer simulated over a regular one and configured with all the required tools needed in a learning experience. Students carry out activities in this environment in which a monitoring scheme has been previously configured. A case study is presented in which a comprehensive set of observations were collected. The data is shown to have significant correlation with student academic achievement thus validating the approach to be used as a prediction mechanism. Finally a prediction model is presented based on those observations with the highest correlation.     

Provision of awareness of learners’ emotions through visualizations in a computer interaction-based environment

One of the challenges of intelligent systems for education is to use low-level data collected in computer environments in the form of events or interactions to infer information with high-level significance using artificial intelligence techniques, and present it through visualizations in a meaningful and effective way. Among this information, emotional data is gaining track in by instructors in their educational activities. Many benefits can be obtained if an intelligent systems can bring teachers with knowledge about their learner’s emotions, learning causes, and learning relationships with emotions. In this paper, we propose and justify a set of visualizations for an intelligent system to provide awareness about the emotions of the learners to the instructor based on the learners’ interactions in their computers. We apply these learner’s affective visualizations in a programming course at University level with more than 300 students, and analyze and interpret the student’s emotional results in connection with the learning process.     

What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction

E-learning is emerging as the new paradigm of modern education. Worldwide, the e-learning market has a growth rate of 35.6%, but failures exist. Little is known about why many users stop their online learning after their initial experience. Previous research done under different task environments has suggested a variety of factors affecting user satisfaction with e-Learning. This study developed an integrated model with six dimensions: learners, instructors, courses, technology, design, and environment. A survey was conducted to investigate the critical factors affecting learners’ satisfaction in e-Learning. The results revealed that learner computer anxiety, instructor attitude toward e-Learning, e-Learning course flexibility, e-Learning course quality, perceived usefulness, perceived ease of use, and diversity in assessments are the critical factors affecting learners’ perceived satisfaction. The results show institutions how to improve learner satisfaction and further strengthen their e-Learning implementation.     

Exploring factors of media characteristic influencing flow in learning through virtual worlds

This study aims to find out factors of media characteristic which are considered to influence flow in learning through virtual worlds. One hundred ninety eight elementary students who are eleven to twelve years old participated in this study. After the exploratory factor analysis, to extract media characteristics of virtual worlds, seventy-eight elementary students who are eleven years old were used in the analysis of exploring relationships between factors influencing flow.     

Development and evaluation of a virtual campus on Second Life: The case of SecondDMI

Video games and new communication metaphors are quickly changing today’s young people habits. Considering the actual e-learning scenarios, embedded in a fully technological enabled environment it is crucial to take advantage of this kind of capabilities to let learning process gain best results.