457,070 research outputs found

    DESIGN OF STUDENT SUCCESS PREDICTION APPLICATION IN ONLINE LEARNING USING FUZZY-KNN

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    Effective evaluation of student performance is crucial. Hence, many kinds of techniques are used such as statistics, physical examination and currently data mining techniques to evaluate student performance. Data mining techniques as known as Educational Data Mining (EDM) collect, process, report and used to find the unseen patterns in the student dataset. EDM uses machine learning techniques to dig out useful data from multiple levels of meaningful hierarchy. Various data from intelligent computer tutors, classic computer based educational systems, online classes, academic data in educational institution, and standar assesment can be process for EDM. This led universities include open and distance learning (ODL) to collect large volume of student and learning data in their learning management systems (LMS). Students in ODL are relatively familiar with LMS and many learning activities such as number of accessing materials, student participation in discussion forum recorded in LMS. The processes of using EDM to improve the quality of educational policy maker with data-based models have become a challange that institutions of higher education face today. Therefore, this study aims to design applications that predict student performance in online learning using machine learning techniques based on EDM. The machine learning technique used in this research is Fuzzy-KNN. Testing using Fuzzy-KNN produces an accuracy of 92.5%

    How does a Gamification Design Influence Studentsā€™ Interaction in an Online Course?

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    This study created and examined a gamification design that aimed at improving studentsā€™ interaction in a graduate level online course. By using a design-based research approach, the study investigated the application of principles from Self-Determination Theory in the gamification design and its influence on studentsā€™ interaction in discussion forums in terms of quantity, interaction dynamic, and interaction quality. The gamification design included a positive feedback system, contextualized in a narrative environment that was based on the original course project design. Participants were 49 students enrolled in the online course in three versions of the course, which were the non-gamification version of the course in the 2016 summer semester (NGC), the prototype gamification version of the course in the 2016 summer semester (PGC), and the revised gamification version of the course in the 2016 summer semester (RGC). Studentsā€™ interaction data in the academic discussion forums were compared with each other. Studentsā€™ gamification performance data were presented and compared between the PGC and the RGC. Moreover, eight students from the RGC participated in semi-structured interviews and shared their experiences and perspectives about the revised gamification design. The results showed that students in the gamified courses posted more messages per week. When students were the facilitators for the week, they were more actively involved in the online discussion. The student facilitators in the gamified courses were more active compared to the student facilitators in the non-gamified course. Second, studentsā€™ interaction was more evenly distributed among students in the gamified courses. On average, students in the gamified courses received comments from more peers than students in the non-gamified course. The class level density scores were higher with smaller centralization scores in the gamified courses. Finally, the RGC discussion transcripts presented more knowledge building features on a weekly basis in comparison with the PGC and the NGC, while overall the online discussion in the three versions of the course fell into the lower phases in the knowledge building conceptual model. Studentsā€™ gamification performance was about the same in the two gamified courses. Nonetheless, the design adjustments made between the two design cycles and during the second cycle improved studentsā€™ participation in several gamification activities. Furthermore, studentsā€™ interaction was more stable during the six weeks in the RGC due to the design adjustments. The semi-structured interviews further revealed the RGC intervieweesā€™ experiences in the course. The positive feedback system satisfied studentsā€™ competence needs. Nonetheless, to what degree their competence needs were satisfied depended on their experiences and understanding of gamification. In pursuit of competence needs, some intervieweesā€™ autonomy needs were undermined. The peer evaluation, dynamic academic discussion, and the authentic course project satisfied studentsā€™ relatedness needs. But additional emotional support from peers was barely sufficient. The study provided an example of gamification design in online courses to improve studentsā€™ interactions in discussion forums. The results suggested a positive feedback system could be added in the course design to improve studentsā€™ performance of the targeted learning activities. The selection of learning activities, the design and development of the gamification elements, and the gamification algorithm should take both the subject matter and studentsā€™ characteristics into consideration. A narrative environment can help align the feedback system with the course context and studentsā€™ actions should result in development of the narrative

    WEB-BASED INTERACTIVE EDOM TO IMPROVE THE PERFORMANCE OF UNISBA BLITAR FKIP LECTURERS

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    This research aims to improve the lecturers' performance of FKIP UNISBA Blitar through the development of Web-Based Interactive EDOM. This is a transformation from the EDOM based paper that has been applied so far, which is considered biased and not appropriate to be applied with the times. The difference between this Interactive EDOM and online EDOM in general is that there is a discussion forum on the account of each lecturer. So lecturers and students can communicate with each other regarding the evaluation of teaching and learning that has been taken in one semester to improve the quality of teaching and learning in the following semester. The method used in this research is Research and Development (research development) with stages; (1) needs analysis and needs assessment, (2) developing media, (3) expert validation, (4) first revision, (5) try-out, (6) second revision, and (7) final product. Involving 2 experts (experts), namely experts in the field of Information Technology by 80% stated valid and 77% valid experts in the field of educational evaluation. The product produced from this study is the Web- based Interactive EDOM using the Edmodo application with the following description: Interactive EDOM consists of multiple choices and The entries between one student and another student are Lecturers in the intended account are encouraged to interact, respond, clarify, fix related EDOM. Each lecturer at FKIP UNISBA Blitar has 1 account in the Interactive EDOM Each student entry will be directly entered into the intended lecturer There is an absence of Interactive EDOM for students whose names are kept The lecturer account will only be visited by students who meet face to face in that semester. &nbsp

    Developing the next generation of occupational therapists: use of learning communities to facilitate student understanding of authentic occupational therapy tasks

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    Background: Active engagement in activities using critical thinking to understand assessment requirements is known to improve students' performance. This project aimed to facilitate occupational therapy students' understanding of professional report writing based on practice education. Method: A series of workshops were run with a cohort of occupational therapy students in their first and then their second year of studies. Workshops focused on students co-creating assessment handy hints with activities progressively graded to increase student independence. Activities included critique of exemplars and student peer-to-peer critique of assignment drafts. Evaluation and ana lysis was through an online survey containing likert scale and open ended questions. Discussion/Outcomes: A higher proportion of responding first year students than second year students felt: 1) the workshops provided clarity of assessment expectations; and 2) exemplars of a high and low grade assisted in understanding assessment standards. A higher proportion of responding second year students than first year students felt: 1) the workshops provided an opportunity to develop and/or demonstrate their ability to contribute effectively to team-based tasks; and 2) the workshops were useful for their learning. Different student engagement styles also emerged: prescriptive, facilitative and se lf directive. Conclusion: Outcomes and reasons for participating in assessment handy hints workshops were different between first and second year and also between students within the same year. This project assists in understanding where resources can be directed in order to facilitate the development of occupational therapy students into our next generation of occupational therapists

    Developing the next generation of occupational therapists: use of learning communities to facilitate student understanding of authentic occupational therapy tasks

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    Background: Active engagement in activities using critical thinking to understand assessment requirements is known to improve students' performance. This project aimed to facilitate occupational therapy students' understanding of professional report writing based on practice education. Method: A series of workshops were run with a cohort of occupational therapy students in their first and then their second year of studies. Workshops focused on students co-creating assessment handy hints with activities progressively graded to increase student independence. Activities included critique of exemplars and student peer-to-peer critique of assignment drafts. Evaluation and ana lysis was through an online survey containing likert scale and open ended questions. Discussion/Outcomes: A higher proportion of responding first year students than second year students felt: 1) the workshops provided clarity of assessment expectations; and 2) exemplars of a high and low grade assisted in understanding assessment standards. A higher proportion of responding second year students than first year students felt: 1) the workshops provided an opportunity to develop and/or demonstrate their ability to contribute effectively to team-based tasks; and 2) the workshops were useful for their learning. Different student engagement styles also emerged: prescriptive, facilitative and se lf directive. Conclusion: Outcomes and reasons for participating in assessment handy hints workshops were different between first and second year and also between students within the same year. This project assists in understanding where resources can be directed in order to facilitate the development of occupational therapy students into our next generation of occupational therapists

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

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    ķ•™ģœ„ė…¼ė¬ø (ė°•ģ‚¬)-- ģ„œģšøėŒ€ķ•™źµ ėŒ€ķ•™ģ› : ģœµķ•©ź³¼ķ•™źø°ģˆ ėŒ€ķ•™ģ› ģœµķ•©ź³¼ķ•™ė¶€(ė””ģ§€ķ„øģ •ė³“ģœµķ•©ģ „ź³µ), 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 ļ¼‘ 1.1. Motivation ļ¼‘ 1.2. Research questions ļ¼” 1.3. Organization ļ¼– Chapter 2. Background ļ¼˜ 2.1. Learning analytics ļ¼˜ 2.2. Collaborative learning ļ¼’ļ¼’ 2.3. Technology-enhanced learning environment ļ¼’ļ¼— Chapter 3. Heterogeneous group formation with online activity data ļ¼“ļ¼• 3.1. Student characteristics for heterogeneous group formation ļ¼“ļ¼– 3.2. Method ļ¼”ļ¼‘ 3.3. Results ļ¼•ļ¼‘ 3.4. Discussion ļ¼•ļ¼™ 3.5. Summary ļ¼–ļ¼” Chapter 4. Real-time dashboard for adaptive feedback in face-to-face CSCL ļ¼–ļ¼— 4.1. Theoretical background ļ¼—ļ¼ 4.2. Dashboard characteristics ļ¼˜ļ¼‘ 4.3. Evaluation of the dashboard ļ¼™ļ¼” 4.4. Discussion ļ¼‘ļ¼ļ¼— 4.5. Summary ļ¼‘ļ¼‘ļ¼” Chapter 5. Real-time detection of at-risk groups in face-to-face CSCL ļ¼‘ļ¼‘ļ¼˜ 5.1. Important learning behaviors of group in collaborative argumentation ļ¼‘ļ¼‘ļ¼˜ 5.2. Method ļ¼‘ļ¼’ļ¼ 5.3. Model performance and influential features ļ¼‘ļ¼’ļ¼• 5.4. Discussion ļ¼‘ļ¼’ļ¼™ 5.5. Summary ļ¼‘ļ¼“ļ¼’ Chapter 6. Conclusion ļ¼‘ļ¼“ļ¼” Bibliography ļ¼‘ļ¼”ļ¼Docto

    A Times Series Study: Student Perceptions on Multimedia Discussion Featuresā€™ Impact on Student Learning and Student Achievement

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    This study sought to determine the studentsā€™ perception of VoiceThread discussion multimedia featuresā€™ impact on their learning and examine the effects of the multimedia features in VoiceThread discussions on student achievement in online classes. The study was conducted at a technical college in southwest Georgia during summer semester 2014. Based on the Operational Report FY 2012 provided to the Business Administrative Technology (BAT) department, this course under study had shown student performance to be consistently lower in online sections (general mean of 63.1%) than traditional, face-to-face sections (general mean of 77.75%). Recommendations were made by the BAT faculty, which included more student interaction and engagement through creative discussions. The Cognitive Theory of Multimedia served as this studyā€™s conceptual framework to support that learning can be more successful if incoming information can be presented in multiple sensory memory channels for learners to process information. The sample for this study included students already pre-registered in two online and two face-to-face sections of the course, which resulted in convenience sampling. This study used a quasi-experimental control group time series research design to determine if a specific treatment influenced student learning and student achievement. Data collection included six assessments, a course evaluation survey, and a multimedia questionnaire. A series of six assessments were used to determine how the multimedia tool, VoiceThread, affected student achievement in online learning. The course evaluation survey was administered to determine how the opinions and attitudes about the course differed between students in the control and treatment groups. Additionally, a multimedia questionnaire was administered to determine the opinions of students in the treatment group regarding the technology and its impact on the course. Descriptive statistics, comparison of means for independent samples (t test), and multivariate analysis of variance (MANOVA) were used for data analysis. Content analysis technique was also used to identify themes and trends for qualitative data collected through open-ended survey items and the comment section of the two surveys. The findings of this study revealed no statistical significant difference between the treatment and control groups, but the student achievement for both groups were comparable based on the assessment mean scores. The course evaluation survey results indicated that the difference between the control and treatment groups was small, but both groups responded very positively about the course. The multimedia questionnaire responses indicated the usage of the multimedia tool, VoiceThread, was mostly positive for the students in the treatment group. Overall, the control and treatment groups were comparable in achievement, attitude, and opinion in the effectiveness of the course. Based on these results the two groups were comparable.TABLE OF CONTENTS | I. | INTRODUCTION 1 | Conceptual Framework 4 | Context 5 | Multimedia Discussion Tool 8 | The Problem 11 | The Purpose 11 | Research Questions 12 | Scope and Limitations 12 | Conceptual and Operational Definitions 13 | Significance of the Study 13 | REVIEW OF THE LITERATURE 15 | METHODOLOGY 25 | Research Design 25 | Population and Sample 26 | Procedures 28 | Instrumentation 30 | Collection of Data 32 | Analysis of Data 33 | FINDINGS 35 | Introduction 35 | Participant Demographics 36 | Pre-Analysis Data Screening 37 | Research Question One Results 38 | Research Question Two Results 43 | Research Question Three Results 49 | Results Summary 57 | SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS 58 | Introduction 58 | Overview of the Study 58 | Description of Population 59 | Procedures 60 | Conclusions 62 | Discussion 62 | Recommendations 67 | REFERENCES 71 | APPENDIX A: 76 | APPENDIX B: 78 | APPENDIX C: 80 | APPENDIX D: 82 | APPENDIX E: 84 | APPENDIX F: 88 | APPENDIX G: 91 | APPENDIX H: 93 | APPENDIX I: 96 | APPENDIX J: 99 | APPENDIX K: 101 | APPENDIX L: 103 |Martinez, Reynaldo L.Leader, Lars F.Whisler, Vesta R.Gerber, Brian L.Ed.D.Educatio

    Online discussion compensates for suboptimal timing of supportive information presentation in a digitally supported learning environment

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    This study used a sequential set-up to investigate the consecutive effects of timing of supportive information presentation (information before vs. information during the learning task clusters) in interactive digital learning materials (IDLMs) and type of collaboration (personal discussion vs. online discussion) in computer-supported collaborative learning (CSCL) on student knowledge construction. Students (N = 87) were first randomly assigned to the two information presentation conditions to work individually on a case-based assignment in IDLM. Students who received information during learning task clusters tended to show better results on knowledge construction than those who received information only before each cluster. The students within the two separate information presentation conditions were then randomly assigned to pairs to discuss the outcomes of their assignments under either the personal discussion or online discussion condition in CSCL. When supportive information had been presented before each learning task cluster, online discussion led to better results than personal discussion. When supportive information had been presented during the learning task clusters, however, the online and personal discussion conditions had no differential effect on knowledge construction. Online discussion in CSCL appeared to compensate for suboptimal timing of presentation of supportive information before the learning task clusters in IDLM

    A Flipped Classroom Redesign in General Chemistry

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    The flipped classroom continues to attract significant attention in higher education. Building upon our recent parallel controlled study of the flipped classroom in a second-term general chemistry course (J. Chem. Educ., 2016, 93, 13ā€“23), here we report on a redesign of the flipped course aimed at scaling up total enrollment while keeping discussion sizes small (i.e.,students), and maintaining equivalent contact hour load for faculty and workload for students. To that end, the course format featured lecture contact pushed outside of the classroom in the form of video lectures (mean duration 13 minutes) paired with online homework sets, and three parallel weekly one-hour discussion sections were held in adjoining lab rooms immediately prior to the three-hour laboratory session. As in our previous design, the discussion sections were led by teaching assistants; however, the weekly discussion meeting was shortened from 75 minutes to 50 minutes, and the primary instructor ā€œfloatedā€ between the three parallel sessions. Two such sessions were held each week, affording a possible enrollment of 144; initial enrollment was 141, with students self-selecting into the course. We examine student performance in and satisfaction with the course using: (1) a pre-test/post-test design based on the paired questions American Chemical Society (ACS) first-term and second-term exams, (2) data on DFW (D, F, withdrawal) rates, and (3) student evaluations
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