The flipped classroom gives students the flexibility to organize their learning, while teachers can monitor their progress analyzing their online activity. In massive courses where there are a variety of activities, automated analysis techniques are required in order to process the large volume of information that is generated, to help teachers take timely and appropriate actions. In these scenarios, it is convenient to classify students into a small number of groups that can receive dedicated support. Using only online activity to group students has proven to be insufficient to characterize relevant groups, because of that this study proposes to understand differences in online activity using differences in course status and learning experience, using data from a programming course (n = 409). The model built shows that learning experience can be categorized in three groups, each with different academic performance and distinct online activity. The relationship between groups and online activity allowed us to build classifiers to detect students who are at risk of failing the course (AUC = 0.84) or need special support (AUC = 0.73), providing teachers with a useful mechanism for predicting and improving student outcomes.
Journal of Computing in Higher Education
The virtual interactive consulting agent system is an online virtual career center that supports freshman students in transition to higher education. This virtual counseling system, based on accumulative empirical knowledge for working students and knowledge about effective career intervention, aims to guide first-year university students in combining study and work effectively. Three main aspects of career interventions are supplied by this virtual interactive consulting agent system: personal assessment, information, and personal encouragement and relatedness. The virtual interactive consulting agent is based on the SimCoach system. The current research includes two studies that examine acceptability and satisfaction from two perspectives: that of the counselors (the experts) and of the consultees (the target consumers). Both studies included 87 participants divided into two research groups: 45 counselors and 42 counseled freshman students. The data were collected through four data collection tools: acceptability and satisfaction questionnaire, an open-ended question, Google Docs, and screen recording applications. The participants’ answers were analyzed using quantitative software. The results show that the majority of the counselors were satisfied with the usability of the system but not with the process of counseling through the virtual agent, with some expressing concern about the impact on the profession. In contrast, most of the consultees were satisfied with the counseling process and some stated that the virtual agent helped them to determine how to integrate work and study more effectively.
High levels of digital media use have become a feature of university lectures. While certainly capable of supporting learning outcomes, studies indicate that, when media use is off-task, it presents as a disruption, distracting both users and those around them from academic tasks. In this study an exploratory, mixed-methods assessment of a media use policy for a semester-long course is presented. This policy divided the lecture theatre into two sections, one for those who wished to use digital devices and one for those who did not. Such a policy empowered students to leverage the value of media, if desired, while affording those who wished not to use media, or be disrupted by their peers’ use of media, a degree of protection from distracting cues. Findings indicate that those who consistently selected the same side performed better than those who moved from side to side. Two post-course focus groups revealed that, while having some limitations, the policy was well received by the participants and heightened their awareness of the possible distractions of off-task media use, enabling them to identify and maintain a strategy for their in-lecture attentional allocation and behaviour.
Massive open online courses (MOOCs) are among the latest e-learning initiative that have gained a wide popularity among many universities. Student dropout in MOOCs is a major concern in the higher education and policy-making communities. Most student dropout is caused by factors outside the institution’s control. In this study, a multiple-criteria decision-making method was used to identify the core factors and possible causal relationships responsible for the high dropout rate in MOOCs. Twelve factors, distributed across four dimensions, related to students’ dropout from online courses were identified from the literature. Then, a total of 17 experienced instructors in MOOCs from different higher education institutions were invited to assess the level of influence of these factors on each other. The results identified six core factors that directly influenced student dropout in MOOCs, these were: academic skills and abilities, prior experience, course design, feedback, social presence, and social support. Other factors such as interaction, course difficulty and time, commitment, motivation, and family/work circumstances were found to play a secondary role in relation to student dropout in MOOCs. The causal relationships between the primary and secondary factors were mapped and described. Outcomes from this study can offer the necessary insights for educators and decision makers to understand the cause–effect relationships between the factors influencing MOOC student dropout, thus providing relevant interventions in order to reduce the high dropout rate.
Learning management systems (LMS) offer quiz tools that help students prepare for examinations. The purpose of this study is to investigate quiz tracking variables typically reported by LMS in relation to student achievement, motivation and learning strategies. The data from 143 undergraduate students comprised quiz tracking variables (number of attempts, completion time, and score), exam scores and responses to the Need for Cognition Scale (NfC), and selected components from the Motivated Strategies for Learning Questionnaire and the Achievement Goal Questionnaire. We hypothesized students retrieving information from memory while taking a quiz would complete the quiz in less time than students who searched for answers in the textbook, and consequently, quiz completion time would correlate with exam performance and key motivational and self-regulatory factors. We found quiz completion time correlated positively with performance-avoidance goal orientation. It correlated negatively with exam performance, NfC, self-efficacy, and effort regulation. The results indicated completion time of low stakes quizzes is associated with achievement-related motivations and reliably predicts achievement on summative exams. We attribute these links to the use of retrieval practice by students who successfully regulate their effort and learning strategies.
What do participants think of today’s MOOCs: an updated look at the benefits and challenges of MOOCs designed for working professionals
Literature on MOOCs has shown that understanding learners’ perspectives in taking MOOCs is critical if a MOOC needs to be successful. Now that MOOCs have been in wide use, in this study we took an updated look at learners’ perspective of taking MOOCs designed for working professionals and course aspects that these MOOC participants found beneficial. General interest in the topic, personal growth and enrichment, relevance to job, and career change were the top reasons for working professionals to enroll in MOOCs. First-time MOOC takers were more likely to seek a certificate, while MOOC veterans may complete most assignments but did not seek for a certificate. Quality materials from a reputable provider remains an important reason for working professionals to enroll in a MOOC. Offering meaningful ways for MOOC participants to interact with instructors and with each other calls for innovative designs than the current discussion forums in a learning management system can offer. This remains to be a big challenge for MOOC designers.
The acceptance of a personal learning environment based on Google apps: the role of subjective norms and social image
The international higher education system should be grounded in an educational approach in which teaching and learning methods aim to transform the student into an active agent in their learning process. The present study aims to learn how intention to use a personal learning environment based on Google applications for supporting collaborative learning is formed, in the context of university student learning. For this purpose, an expansion of the technology acceptance models was proposed including subjective norms and social image. The model was empirically evaluated using survey data collected from 267 students from a marketing management degree course, on which Google applications (apps) were used to design a learning environment to support project work and learning. The results show the suitability of the extended TAM to explain the intention to use Google apps as a personal learning environment in the university context. More specifically, subjective norms contributed to the indirect effect on the intention to use Google apps through social image and had a substantial positive influence on the social image. Meanwhile, social image had a significant positive direct effect on perceived usefulness. The results of the present study have a series of practical implications for the higher education sector.
Preservice teachers’ Web 2.0 experiences and perceptions on Web 2.0 as a personal learning environment
To explore students’ use of Web 2.0 tools and their perceptions of using Web 2.0 as a personal learning environment (PLE), quantitative surveys (n = 113) and interviews (n = 12) were conducted. In the survey, we identified that students already have familiarity with using Web 2.0 tools, as well as a positive attitude toward using Web 2.0 for learning. However, in the interview, students referenced challenges with using Web 2.0 in their PLE. The results imply that there are gaps between students’ perceived comfort and familiarity with using Web 2.0 tools and their readiness to be an active and successful designer for Web 2.0-based PLEs. This research also identified that there may be other factors influencing students’ building PLEs with Web 2.0 tools including the knowledge of different tools, the abilities of identifying learning objectives and learning styles, access to the tools, motivation, and knowing how to locate the correct information through students’ interviews.
Students’ goal-setting skills are highly related to their academic learning performance and level of motivation. A review of the literature demonstrated limited research on both applicable goal-setting strategies in higher education and the support of technology in facilitating goal-setting processes. Addressing these two gaps, this study explored the use of digital badges as an innovative approach to facilitate student goal-setting. The digital badge is a digital technology that serves as both a micro-credential and a micro-learning platform. A digital badge is a clickable badge image that represents an accomplished skill or knowledge and includes a variety of metadata such as learning requirements, instructional materials, endorsement information, issue data and institution, which allows the badges to be created, acquired and shared in an online space. In higher education, digital badges have the potential for assisting students by promoting strategic management of the learning process, encouraging persistence and devoted behavior to learning tasks, and improving learning performance. A qualitative multiple case study design (n = 4) was used to answer the research question: how did the undergraduate student participants in this study use digital badges to facilitate their goal-setting process throughout a 16-week hybrid course? Results from this study contribute to understanding how to effectively integrate digital badges to meaningfully improve self-regulated learning in higher education.
How lecturers neutralize resistance to the implementation of learning management systems in higher education
The aim of the study was to investigate neutralisation techniques used by lecturers to justify their resistance behaviours during the implementation of learning management systems (LMS) in higher educational institutions (HEIs). Moreover, we explored why lecturers employed such neutralisation techniques to justify their resistance behaviours. A number of studies identified resistance as a barrier to successful implementation of technology in HEIs. However, there is a dearth of literature on the choice of neutralisation techniques employed by lecturers to justify such resistance behaviours. Understanding the logic behind the choice of neutralisation techniques could ensure effective management strategies towards user resistance, which could further assist to improve technology uptake in HEIs. The study draws from Bourdieu’s theory of practice (ToP) as a lens to investigate the logic behind the use of certain neutralisation techniques to justify user resistance. The research used cross-sectional data from semi-structured interviews and participant observations of a single in-depth case setting. The most common neutralisation technique used by lecturers was condemn the condemners followed by denial of responsibility, denial of injury, and appeal to higher loyalties. Findings suggest that the habitus and capital of lecturers significantly influence the choice of techniques to justify resistance. Lecturers tended to neutralise before they resisted, such that they prepared themselves to justify any deviance well in advance in case they got caught. Integration of ToP and Neutralisation theory enriches theorisation of user resistance, enabling development of mechanisms that could effectively manage lecturer resistance behaviours to improve uptake of LMS in HEIs.
Examining barriers and desired supports to increase faculty members’ use of digital technologies: perspectives of faculty, staff and administrators
Faculty members at Institutions of Higher Education have access to more technology than ever before and are teaching college and university students who use technology constantly in their personal lives. However, barriers still exist that limit how technology can enhance teaching at colleges and universities. This study examined the perspectives of faculty members, administrators, and technology support staff to examine the barriers and desired supports related to faculty members’ use of technology in their teaching. Findings indicated that the primary barriers were the amount of time needed to learn technologies and determine how to teach with them as well as the tension between focusing on teaching and other job responsibilities, including research. Desired supports included one-on-one, just-in-time support that was efficient and personalized to meet the needs of faculty members.
The aim of the present work is to contribute to the study of use intention for technologies related to the increasingly popular massive open online courses (MOOCs). Informed by a scientific literature review, the work proposes a behavioral model to explain use intention via various constructs. The results of the analysis verify the effect of user perceived satisfaction and autonomous motivation as the strongest predictors of use intention. The analysis also shows that perceived satisfaction is affected by the quality of the course, its entertainment value and its usefulness. The latter variable is also a major factor in explaining user emotions. The study provides an original focus in the study of perceived satisfaction and MOOC use intention by extending the models proposed in previous published literature in this emerging field.
This study examined the role motivational dispositions had on completing a massive open online course (MOOC) using identifiable data from 10,726 students who enrolled in an iteration of the HarvardX MOOC, Super Earths and Life. As part of the course registration process, learners had the option to complete a pre-course survey and self-report information including their level of education, gender and registration motivations. Using these pre-course survey responses, latent profiles linked to learners’ course performance were created. Results showed education background, gender, and motivation were all significantly related to students’ performance. Furthermore, students with intrinsic motivational dispositions performed better than students with extrinsic dispositions, and females performed better than males.
Exploring instructors’ perspectives, practices, and perceived support needs and barriers related to the gamification of MOOCs
This study explored instructors’ perceptions, interest, self-efficacy, perceived barriers, and support needs regarding gamification in MOOCs. Both quantitative and qualitative data were collected from an online survey and follow-up interviews. Most participants showed interest in gamification and indicated that they would consider utilizing gaming elements in their future MOOCs. Interestingly, they wanted to gamify their MOOCs mostly to increase social interactions and student retention. Significant differences in self-efficacy and perceptions of gamification were found between younger participants and older participants. The results also revealed significant differences in interest and self-efficacy between participants with prior experience with gamification and those without prior experience. The major barriers to gamifying MOOCs included lack of time, limited knowledge, lack of funding, lack of fit between gamification and the course content, concerns about students’ perceptions of gamification, and concerns regarding the negative effects of gamification. Participants reported that they would need time and funding, guidance from gamification experts, examples of gamified MOOCs, more flexible MOOC platforms in order to successfully gamify their MOOCs.
The effects of social and cognitive cues on learning comprehension, eye-gaze pattern, and cognitive load in video instruction
Students experience challenges when understanding visual information in multimedia learning. Specifically, immersive multimedia environments, such as virtual reality increase the likelihood that students undergo distractions in which information seeking during system-paced instruction occurred. Although previous studies have reviewed various cue designs to yield students’ higher attention, skepticism still exists regarding which ways cue designs can support their learning comprehension in video instruction. For this study, we sampled a total of 64 undergraduates in a university. Using video instruction performed by an animated pedagogical agent (APA), this study examined the effect of social (i.e., an APA’s conversational gestures) and cognitive (i.e., visual cue) cues on students’ learning comprehension and eye-gaze data within types of visual information (text and pictorial). Also, this study investigated how both cues promoted students’ cognitive load overall. Specific to text information processing, the results of the study confirmed that the negative prime effect of social cues undermined students’ learning comprehension and increased their cognitive load, whereas cognitive cues appeared to be supportive in video instruction. Also, this study found that students’ different visual-attention patterns appeared in pictorial information processing. In terms of pictorial information processing, the study finding implies that whereas social cues caused visual distractions and lowered learning comprehension, cognitive cues as visual cues helped learners to integrate pictorial information via visuospatial clues. Conclusively, we reported several design implications derived from the study findings.
Ideally, instruction should be delivered in a way that reduces the processing of information that does not contribute to learning (extraneous load) and increases cognitive processing that contributes to learning (germane load). One way students might effectively manage extraneous load is through specific video lecture viewing strategies to control the flow of information. Extant research provides conflicting perspectives regarding the role of viewing strategies within video lectures in improving learning. This study analyzed survey responses from a group of university students (n = 2012) participating in online classes in South Korea and looked at the mediating effect of video lecture viewing strategies on the relationship between extraneous load and germane load. The results showed that viewing strategies mediated the relationship between extraneous load and germane load. When viewing strategies were added to the model, the large negative relationship between extraneous load and germane load reversed to become a small positive relationship, implying that the negative correlation between extraneous load and germane load can be largely mitigated by students engaging in specific viewing strategies to better understand the content.
Problem-solving is one of the biggest challenges that students can find in an Engineering degree. Information and communication technologies are of great use in this regard, providing learners with tools that complement their study and facilitate skills acquisition. A good strategy to enhance student motivation towards problem-solving is to use engaging and interactive gamification techniques. To achieve this, we developed a web board game with six categories of problems for the Industrial Systems Optimization Techniques subject, which is part of the Industrial Organization Engineering curriculum at Madrid Open University. The game relies on case-study simulators for six categories of problems in such way that the cases presented to the students are always different. Students receive instant feedback about the accurateness of their response as well as the correct solution. The results of the experience, based on data obtained and surveys carried out, indicate that the board game is dynamic and motivational as well as academically encouraging.
In this full review paper, the recent emerging trends in E-learning Assessment have been reviewed and explored to address the recent topics and contributions in the era of Distance Education. This includes a set of rigorously reviewed world-class manuscripts addressing and detailing state-of-the-art, frameworks and techniques research projects in the area of E-learning Assessment, using different approaches such as Blockchain, Gamification, Process Mining, among others. Based on this systematic review, we have put some recommendations and suggestions for researchers, practitioners and scholars to improve their research quality in this area.
In the higher education sector, a new era has begun with the advent of ubiquitous learning environments. Ubiquitous learning tools allow improving context-aware as well as learning experiences by offering seamless availability regardless of location all the time. They also help in establishing effortless interaction between authentic and digital learning resources and at the same time offering personalised learning opportunities as well. There are numerous available ubiquitous e-learning tools that can be employed in higher education. E-learning tools also offer training and higher education to many students that have different higher educational levels and come from diverse cultural backgrounds. However, if the capabilities of e-learning are underestimated, these may not be successful in higher education. Some of the people lack understanding about the limitations and weaknesses of e-learning, while some may have superfluous expectations. In this paper, various e-learning tools like Wikipedia, MOODLE, Web 2.0, Web 3.0 and Blackboard have been evaluated. We also comment on key aims regarding each tool and investigate the disadvantages and advantages. Based on this analysis, a global view regarding the current as well as future tendencies pertaining to ubiquitous e-learning tools is obtained and thus possible key comments are provided for employing e-learning tools like MOODLE, Web 2.0 and Web 3.0 in the classroom. Based on our teaching experience, MOODLE was found to be efficient in the development of e-learning. MOODLE was favoured by a majority of authors and practitioners rather than Blackboard. However, MOODLE cannot be considered a fully pure social software since it does not include social networks. In this review, the scope of employing ubiquitous learning environments has been presented in higher education contexts. However, it increases the requirement for transparent research that shows practical implications to generalise future development processes. Moreover, it was shown that e-learning 3.0 is one amongst the key trends employing Web 3.0 tools for social learning. Also, on the Internet, quick incorporation of new services into existing applications like integrating Wiki with Web 3.0 can be done easily. The primary risk here would be the fact that lecturers and students are not fully aware that these web services are not controlled by their universities. Since these servers have been installed in many different countries, the principles and privacy laws vary from country to country.
A supervised learning framework: using assessment to identify students at risk of dropping out of a MOOC
Both educational data mining and learning analytics aim to understand learners and optimise learning processes of educational settings like Moodle, a learning management system (LMS). Analytics in an LMS covers many different aspects: finding students at risk of abandoning a course or identifying students with difficulties before the assessments. Thus, there are multiple prediction models that can be explored. The prediction models can target at the course also. For instance, will this activity assessment engage learners? To ease the evaluation and usage of prediction models in Moodle, we abstract out the most relevant elements of prediction models and develop an analytics framework for Moodle. Apart from the software framework, we also present a case study model which uses variables based on assessments to predict students at risk of dropping out of a massive open online course that has been offered eight times from 2013 to 2018, including a total of 46,895 students. A neural network is trained with data from past courses and the framework generates insights about students at risk in ongoing courses. Predictions are then generated after the first, the second, and the third quarters of the course. The average accuracy that we achieve is 88.81% with a 0.9337 F1 score and a 73.12% of the area under the ROC curve.