Student Engagement in Aviation Moocs: Identifying Subgroups and Their Differences

The purpose of this study was to expand the current understanding of learner engagement in aviation-related Massive Open Online Courses (MOOCs) through cluster analysis. MOOCs, regarded for their low- or no-cost educational content, often attract thousands of students who are free to engage with the provided content to the extent of their choosing. As online training for pilots, flight attendants, mechanics, and small unmanned aerial system operators continues to expand, understanding how learners engage in optional aviation-focused, online course material may help inform course design and instruction in the aviation industry. In this study, Moore’s theory of transactional distance, which posits psychological or communicative distance can impede learning and success, was used as a descriptive framework for analysis. Archived learning analytics datasets from two 2018 iterations of the same small unmanned aerial systems MOOC were cluster-analyzed (N = 1,032 and N = 4,037). The enrolled students included individuals worldwide; some were affiliated with the host institution, but most were not. The data sets were cluster analyzed separately to categorize participants into common subpopulations based on discussion post pages viewed and posts written, video pages viewed, and quiz grades. Subgroup differences were examined in days of activity and record of completion. Pre- and postcourse survey data provided additional variables for analysis of subgroup differences in demographics (age, geographic location, education level, employment in the aviation industry) and learning goals. Analysis of engagement variables revealed three significantly different subgroups for each MOOC. Engagement patterns were similar between MOOCs for the most and least engaged groups, but differences were noted in the middle groups; MOOC 1’s middle group had a broader interest in optional content (both in discussions and videos); whereas MOOC 2’s middle group had a narrower interest in optional discussions. Mandatory items (Mandatory Discussion or Quizzes) were the best predictors in classifying subgroups for both MOOCs. Significant associations were found between subgroups and education levels, days of activity, and total quiz scores. This study addressed two known problems: a lack of information on student engagement in aviation-related MOOCs, and more broadly, a growing imperative to examine learners who utilize MOOCs but do not complete them. This study served as an important first step for course developers and instructors who aim to meet the diverse needs of the aviation-education community

The design, implementation and evaluation of a web-based learning environment for distance education

In this study, the need was emphasised to investigate the effects of using the Web in teaching students at a distance using a multi-level evaluation framework. A Web-based learning environment was designed, developed, implemented and evaluated for this purpose. Constructivist epistemology provided the basis for developing various components and developing problem-centred and interactive activities. Management, tutorial, interaction and support components were designed to work with each other to construct the learning environment, deliver course content, facilitate interaction and monitor student progress.A methodology was designed to describe and assess the learning environment in terms of access (standardisation, speed, resources, the tutor and peers), costs (types, structure, factors influencing, etc.), teaching and learning functions (quality of course objectives, materials and resources, learning approach and student achievement), interactivity (quantity and quality of student-tutor and student-peer interaction), user-friendliness (user-interface design, ease of use and navigation design) and organisational issues. The learners were Egyptian first-grade secondary school students (32), assigned randomly, and the topic selected for the course being developed was mathematics. Feedback was obtained from both learners and experts in distance education and on-line learning during the developmental and field-testing of the learning environment. Quantitative and qualitative methods (on-line student and expert questionnaires, students' logs, performance in formative evaluation, content analysis of peer discussions, achievement test and cost-analysis) were combined to gain insights into students' satisfaction with the different instructional and technical features and capabilities of the learning environment, achievement of course objectives in comparison with conventional classroom students, factors influencing their learning and perceptions and the unit cost per student study hour.The results indicated that although the learning environment and course materials were accessible, interactive, well-structured, user-friendly and achievement was successful for the on-line group, no significant differences were identified between the on-line students and traditional classroom students in overall achievement or achievement of low-order and high-order learning objectives. In addition, it is unlikely any cost saving would be made from shifting to the Internet to deliver instruction and many major factors were found to influence the development and support costs of on-line learning

Inclusive Intelligent Learning Management System Framework

Machado, D. S-M., & Santos, V. (2023). Inclusive Intelligent Learning Management System Framework. International Journal of Automation and Smart Technology, 13(1), [2423]. https://doi.org/10.5875/ausmt.v13i1.2423The article finds context and the current state of the art in a systematic literature review on intelligent systems employing PRISMA Methodology which is complemented with narrative literature review on disabilities, digital accessibility and legal and standards context. The main conclusion from this review was the existing gap between the available knowledge, standards, and law and what is put into practice in higher education institutions in Portugal. Design Science Research Methodology was applied to output an Inclusive Intelligent Learning Management System Framework aiming to help higher education professors to share accessible pedagogic content and deliver on-line and presential classes with a high level of accessibility for students with different types of disabilities, assessing the uploaded content with Web content Accessibility Guidelines 3.0, clustering students according to their profile, conscient feedback and emotional assessment during content consumption, applying predictive models and signaling students at risk of failing classes according to study habits and finally applying a recommender system. The framework was validated by a focus group to which experts in digital accessibility, information systems and a disabled PhD graduate.publishersversionpublishe

Utilizing Online Activity Data to Improve Face-to-Face Collaborative Learning in Technology-Enhanced Learning Environments

학위논문 (박사)-- 서울대학교 대학원 : 융합과학기술대학원 융합과학부(디지털정보융합전공), 2019. 2. Rhee, Wonjong .We live in a flood of information and face more and more complex problems that are difficult to be solved by a single individual. Collaboration with others is necessary to solve these problems. In educational practice, this leads to more attention on collaborative learning. Collaborative learning is a problem-solving process where students learn and work together with other peers to accomplish shared tasks. Through this group-based learning, students can develop collaborative problem-solving skills and improve the core competencies such as communication skills. However, there are many issues for collaborative learning to succeed, especially in a face-to-face learning environment. For example, group formation, the first step to design successful collaborative learning, requires a lot of time and effort. In addition, it is difficult for a small number of instructors to manage a large number of student groups when trying to monitor and support their learning process. These issues can amount hindrance to the effectiveness of face-to-face collaborative learning. The purpose of this dissertation is to enhance the effectiveness of face-to-face collaborative learning with online activity data. First, online activity data is explored to find whether it can capture relevant student characteristics for group formation. If meaningful characteristics can be captured from the data, the entire group formation process can be performed more efficiently because the task can be automated. Second, learning analytics dashboards are implemented to provide adaptive support during a class. The dashboards system would monitor each group's collaboration status by utilizing online activity data that is collected during class in real-time, and provide adaptive feedback according to the status. Lastly, a predictive model is built to detect at-risk groups by utilizing the online activity data. The model is trained based on various features that represent important learning behaviors of a collaboration group. The results reveal that online activity data can be utilized to address some of the issues we have in face-to-face collaborative learning. Student characteristics captured from the online activity data determined important group characteristics that significantly influenced group achievement. This indicates that student groups can be formed efficiently by utilizing the online activity data. In addition, the adaptive support provided by learning analytics dashboards significantly improved group process as well as achievement. Because the data allowed the dashboards system to monitor current learning status, appropriate feedback could be provided accordingly. This led to an improvement of both learning process and outcome. Finally, the predictive model could detect at-risk groups with high accuracy during the class. The random forest algorithm revealed important learning behaviors of a collaboration group that instructors should pay more attention to. The findings indicate that the online activity data can be utilized to address practical issues of face-to-face collaborative learning and to improve the group-based learning where the data is available. Based on the investigation results, this dissertation makes contributions to learning analytics research and face-to-face collaborative learning in technology-enhanced learning environments. First, it can provide a concrete case study and a guide for future research that may take a learning analytics approach and utilize student activity data. Second, it adds a research endeavor to address challenges in face-to-face collaborative learning, which can lead to substantial enhancement of learning in educational practice. Third, it suggests interdisciplinary problem-solving approaches that can be applied to the real classroom context where online activity data is increasingly available with advanced technologies.Abstract i Chapter 1. Introduction １ 1.1. Motivation １ 1.2. Research questions ４ 1.3. Organization ６ Chapter 2. Background ８ 2.1. Learning analytics ８ 2.2. Collaborative learning ２２ 2.3. Technology-enhanced learning environment ２７ Chapter 3. Heterogeneous group formation with online activity data ３５ 3.1. Student characteristics for heterogeneous group formation ３６ 3.2. Method ４１ 3.3. Results ５１ 3.4. Discussion ５９ 3.5. Summary ６４ Chapter 4. Real-time dashboard for adaptive feedback in face-to-face CSCL ６７ 4.1. Theoretical background ７０ 4.2. Dashboard characteristics ８１ 4.3. Evaluation of the dashboard ９４ 4.4. Discussion １０７ 4.5. Summary １１４ Chapter 5. Real-time detection of at-risk groups in face-to-face CSCL １１８ 5.1. Important learning behaviors of group in collaborative argumentation １１８ 5.2. Method １２０ 5.3. Model performance and influential features １２５ 5.4. Discussion １２９ 5.5. Summary １３２ Chapter 6. Conclusion １３４ Bibliography １４０Docto

Knowledge mentoring as a framework for designing computer-based agents for supporting musical composition learning

An approach to the design of teaching agents in problem-seeking domains - that is based on a systematic relationship between theoretical framework, analysis of empirical data, computational model and computational implementation - has been developed. The theoretical framework, called the Knowledge Mentoring framework (KMf), was developed to investigate how studies of dialogue and interaction can be exploited in a practical way by designers of computer-based teaching agents. A particular focus was the following musical education problem: when interacting with a computer-based music system, many students do not spontaneously reflect on their activity, they often need to be encouraged to do this. The KMf provides a taxonomy and definitions of the pedagogical goals involved in a 'mentoring' style of teaching. Mentoring is an approach to teaching that aims to support learners' creative, metacognitive and critical thinking, these being essential to musical composition and other open-ended, problem-seeking domains. This theoretical framework was used to guide the analysis and modelling of data produced by an empirical study of human teacher-learner interactions. Information on the temporal ordering of teacher-learner interactions was revealed (modelled as. state transition networks and a mentoring script). Findings from the analysis also included a pause taxonomy (that provided evidence of a link between pause length and learner ability) and the occurrence of reciprocal modelling (where participants in learning interactions built up models of the other participants' expectations). The theoretical framework and the analysis findings were then used to develop a computational model for teaching agents in problem-seeking domains. Aspects of our theory, analysis findings and computational model were incorporated into a computational implementation: a pre-prototype teaching agent called MetaMuse. A Cooperative Evaluation of MetaMuse with teacher-composers showed that it had the potential to promote creative reflection in learners

Implementation of ECRIF framework to improve speaking skills in a1 level students at Instituto Tecnológico T´Sachila in Santo Domingo 2021

To implement the ECRIF framework to improve speaking skills in A1 level students at Instituto Tecnológico T´sachila in Santo Domingo 2021.This research work aimed to review the state of the art of the ECRIF framework to be applied to improve the oral production of the English students at the T’sachila Institute. The information was collected using field research instruments such as an interview and a survey which helped identify the problems of the first-level A1 English students and teachers. With this vital information, the researcher identified the most appropriate speaking strategies to improve the students’ speaking skills to encourage and motivate students' interest in practicing their speech. The study had a quasi-experimental design that applied a pre-test and post-test. A proposal based on the ECRIF framework with speaking strategies such as group conversations, dialogues, debates, and picture descriptions were applied during the intervention. As a result of this research, there was a notable improvement in the student's pronunciation and intonation, lexical range, appropriateness of linguistic choices, grammatical accuracy, fluency, communications strategies, cohesion, and coherence according to the A1 level of English based on the CEFR of languages. Discussion of the research questions, conclusions, and recommendations are based on the applications and implications of this study.Maestrí

Examination of asynchronous volumetric and frequency communication patterns in online courses and their impact on adult learner satisfaction

The purpose of this study was to investigate the relationship of online discussion board interactions of adult learners and their satisfaction with their experience. Specifically, this study\u27s objectives were to examine the asynchronous volumetric and frequency textual communication patterns through online discussion boards and the association to adult learner satisfaction for 102 electronically surveyed adult learners at a mid-western university during the 2005-2006 academic year. Highly reliable (Cronbach alpha = 0.97) and valid data were collected from a learner satisfaction form developed specifically for the outcome variable o f this study. Exploratory factor analysis provided evidence that the data collected from the form were asymmetrically sub-structured into four distinct factors. Communication constructs of momentum, force, and energy were created from physical parameters and determined to be the main predictor variables in this study. The communication constructs were significantly related to the outcome of learner satisfaction and collectively constituted the structural core of this study’s model as determined by correlations and linear regression modeling. Moderator variables of learner prior experience and learner prior satisfaction were found to create a highprecision model of asynchronous volumetric and frequency communication patterns and learner satisfaction through correlations and interaction effects in regression analysis. The study provides core and high-precision models that link asynchronous textual communication for discussion boards in online courses to adult learner satisfaction

Students' perceptions of and performance in online learning : an examination of the community inquiry model

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Undergraduate Students' Experiences of Their Mathematical Identity

This research study explored how undergraduate mathematics students perceive themselves as capable mathematics learners and whether gender differences exist in the undergraduates students' perceptions. The research was framed by three approaches of understanding identity: self-efficacy, environment, and four faces of learner's identity. A mixed methods approach to the study was used where data were collected from interviews and an online questionnaire. Data analysis revealed that undergraduate mathematics students' perceptions of their mathematical identity as capable mathematics learners are influenced by their perceptions of their experiences such as: (a) perceptions of having previous knowledge of the course, (b) being able teach others and others understand it, (c) being recognized by their professors, (d) contributing and fitting in, (e) having opportunities to interact with their peers, and (f) being able to fit in with their image of a capable mathematics learner