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Predicting Student Success in a Self-paced Mathematics MOOC

Predicting Student Success in a Self-paced Mathematics MOOC PDF Author: James Allan Cunningham
Publisher:
ISBN:
Category : Algebra
Languages : en
Pages : 115

Book Description
While predicting completion in Massive Open Online Courses (MOOCs) has been an active area of research in recent years, predicting completion in self-paced MOOCS, the fastest growing segment of open online courses, has largely been ignored. Using learning analytics and educational data mining techniques, this study examined data generated by over 4,600 individuals working in a self-paced, open enrollment college algebra MOOC over a period of eight months. Although just 4% of these students completed the course, models were developed that could predict correctly nearly 80% of the time which students would complete the course and which would not, based on each student’s first day of work in the online course. Logistic regression was used as the primary tool to predict completion and focused on variables associated with self-regulated learning (SRL) and demographic variables available from survey information gathered as students begin edX courses (the MOOC platform employed). The strongest SRL predictor was the amount of time students spent in the course on their first day. The number of math skills obtained the first day and the pace at which these skills were gained were also predictors, although pace was negatively correlated with completion. Prediction models using only SRL data obtained on the first day in the course correctly predicted course completion 70% of the time, whereas models based on first-day SRL and demographic data made correct predictions 79% of the time.

Predicting Student Success in a Self-paced Mathematics MOOC

Predicting Student Success in a Self-paced Mathematics MOOC PDF Author: James Allan Cunningham
Publisher:
ISBN:
Category : Algebra
Languages : en
Pages : 115

Book Description
While predicting completion in Massive Open Online Courses (MOOCs) has been an active area of research in recent years, predicting completion in self-paced MOOCS, the fastest growing segment of open online courses, has largely been ignored. Using learning analytics and educational data mining techniques, this study examined data generated by over 4,600 individuals working in a self-paced, open enrollment college algebra MOOC over a period of eight months. Although just 4% of these students completed the course, models were developed that could predict correctly nearly 80% of the time which students would complete the course and which would not, based on each student’s first day of work in the online course. Logistic regression was used as the primary tool to predict completion and focused on variables associated with self-regulated learning (SRL) and demographic variables available from survey information gathered as students begin edX courses (the MOOC platform employed). The strongest SRL predictor was the amount of time students spent in the course on their first day. The number of math skills obtained the first day and the pace at which these skills were gained were also predictors, although pace was negatively correlated with completion. Prediction models using only SRL data obtained on the first day in the course correctly predicted course completion 70% of the time, whereas models based on first-day SRL and demographic data made correct predictions 79% of the time.

Education & Science 2022

Education & Science 2022 PDF Author: Muslim ALANOĞLU
Publisher: Efe Akademi Yayınları
ISBN: 6258121020
Category : Cooking
Languages : en
Pages : 214

Book Description
ANALYSIS OF RESEARCH ON 21ST CENTURY SKILLS: 2015-2022 Erhan ŞENGEL, Sevim AYDIN MACHINE LEARNING APPLICATIONS IN EDUCATION: A LITERATURE REVIEW Mustafa AKSOĞAN, Bünyamin ATICI DESIGN THINKING IN EDUCATION Rüveyda KARAMAN DÜNDAR DIGITAL REPUTATION OF SCHOOLS ACCORDING TO EDUCATION STAKEHOLDERS Esra KAYA ATICI, Songül KARABATAK WHAT HIGER EDUCATION STUDENTS THINK ABOUT ONLINE LEARNING IN THE NEW NORMAL PERIOD OF THE COVID-19 PANDEMIC? Niyazi AKTAŞ, Erhan ŞENGEL WRITING ASSESSMENT OF EFL (ENGLISH AS A FOREIGN LANGUAGE) LEARNERS IN ONLINE EDUCATION H. Kübra ER A QUALITATIVE STUDY ON THE CONTRIBUTIONS OF THE PRACTICUM EXPERIENCE TO PROSPECTIVE EFL TEACHERS’ PROFESSIONAL DEVELOPMENT Gülşah KÜLEKÇİ DESIGN MODEL FOR FOREIGN LANGUAGE PREPARATORY CLASSES Mehmet DOĞAN, İsmail GÜLER, Nazlı KOÇ RE-EVALUATION OF NOUN PHRASE ACCESSIBILITY HIERARCHY (NPAH): DOES IT WORK IN TURKISH EFL CONTEXT? Emrah ŞAVRAN DETERMINING THE ATTITUDES OF TOURISM MANAGEMENT DEPARTMENT STUDENTS TOWARDS ENGLISH AND A SOLUTION-ORIENTED APPROACH TO PROBLEMS Osman OZDEMIR AN ANALYSIS OF SECONDARY SCHOOL STUDENTS’ SENSE OF SCHOOL BELONGING IN TERMS OF VARIOUS VARIABLES Emel SARITAS

Digital Innovations in Healthcare Education and Training

Digital Innovations in Healthcare Education and Training PDF Author: Stathis Th Konstantinidis
Publisher: Academic Press
ISBN: 0128131454
Category : Medical
Languages : en
Pages : 214

Book Description
Digital Innovations in Healthcare Education and Training discusses and debates the contemporary knowledge on the evolution of digital education, learning and the web and its integration and role within modern healthcare education and training. The book encompasses topics such as healthcare and medical education theories and methodologies, social learning as a formal and informal digital innovation, and the role of semantics in digital education. In addition, it examines how simulation, serious games, and virtual patients change learnings in healthcare, and how learning analytics and big data in healthcare education leads to personalized learning. Online pedagogy principles and applications, participatory educational design and educational technology as health intervention are bridged together to complement this collaborative effort. This book is a valuable resource for a broad audience, both technical and non-technical, including healthcare and medical tutors, health professionals, clinicians, web scientists, engineers, computer scientists and any other relevant professional interested in using and creating digital innovations for healthcare education and training. Provides contemporary knowledge on the evolution of learning technologies and the web and its integration and role within modern healthcare education and training Discusses the latest digital innovation in healthcare education and training, thus enabling all type of readers to apply best practices Encompasses a cross-theme, scholarly explanation based on successful cases which provides a deep knowledge experience into digital innovation in healthcare education and training

Factors Related to Successful Completion of Developmental Mathematics Courses

Factors Related to Successful Completion of Developmental Mathematics Courses PDF Author: Jason Bagley
Publisher:
ISBN:
Category :
Languages : en
Pages :

Book Description
Dweck's mindset, math anxiety, multiplication skills, and attitudes toward mathematics were measured and used to predict student success in developmental math courses as measured by percent of points earned and pass rates. A pre/post survey design research study was conducted with students in Math 990, Math 1010, and Math 1050 at Utah State University. Data were analyzed using linear regression to predict percent of points earned and logistic regression to predict pass rates. Math anxiety was found to have a large and statistically signicant negative effect on student course grades and pass rates. Dweck's mindset was found to be a strong predictor of student success. Multiplication skills were related to student success as measured in percent of points earned in the course, particularly in beginning algebra courses. Students' attitudes toward mathematics, particularly perceived ability and interest in mathematics, predicted very large differences in student achievement and pass rates. The data supported claims that anxiety impacts students' ability to do mathematics and achieve. Dweck's research on mindset and previous research was also supported through the analyses performed. Evidence supports previously made attempts at interventions targeted toward student anxiety and changing students' mindset, as noted by Hattie and Dweck.

Predicting Success in a Mathematics Course

Predicting Success in a Mathematics Course PDF Author: Zeynep Seven Demir
Publisher:
ISBN:
Category : College dropouts
Languages : en
Pages : 84

Book Description
Retention is a genuine, valid apprehension for many two-year colleges and four-year universities in the United States. As many as 1 in 3 first-year students do not return for the sophomore year due to variety of reasons, such as family problems, insufficient funds, and academic challenges (Freshman Retention Rate, n.d.). Given these circumstances, many successful colleges, including Texas Woman's University (TWU), look to implement strategies to maximize the retention rate by admitting students who appear to have a good chance of success. There are several methods to identify and better understand the impact of various practices on college student retention and persistence to degree completion. A critical step on the student pathway is the placement of students as they enter college. To facilitate the journey, an advisor can use the scores from a placement exam to decide an appropriate level course for a student’s current knowledge level. Validity studies for these exams are essential for institutions to evaluate cut-off scores and ensure students are appropriately placed in courses that match their skill level. The main purpose of this study is to compare the efficacy and effectiveness of two placement tests: Accuplacer and the historical placement rules of the TWU departmental Mathematics exam. Efficacy ? refers to whether a product or intervention has a positive influence on learning, such as reducing wrong answers, increasing retention rates, or raising final exam scores. Effectiveness measures the size of the educational development of a product or educational intervention. After the analysis, we can determine whether Accuplacer or the TWU departmental Mathematics exam is the better prognosticator for placing students in classes appropriate for their skill level.

ECEL 2020 19th European Conference on e-Learning

ECEL 2020 19th European Conference on e-Learning PDF Author: Prof. Dr.-Ing. Carsten Busc,
Publisher: Academic Conferences International Limited
ISBN: 1912764792
Category : Education
Languages : en
Pages :

Book Description


Utilizing Learning Analytics to Support Study Success

Utilizing Learning Analytics to Support Study Success PDF Author: Dirk Ifenthaler
Publisher: Springer
ISBN: 331964792X
Category : Education
Languages : en
Pages : 341

Book Description
Students often enter higher education academically unprepared and with unrealistic perceptions and expectations of university life, which are critical factors that influence students’ decisions to leave their institutions prior to degree completion. Advances in educational technology and the current availability of vast amounts of educational data make it possible to represent how students interact with higher education resources, as well as provide insights into students’ learning behavior and processes. This volume offers new research in such learning analytics and demonstrates how they support students at institutions of higher education by offering personalized and adaptive support of their learning journey. It focuses on four major areas of discussion: · Theoretical perspectives linking learning analytics and study success. · Technological innovations for supporting student learning. · Issues and challenges for implementing learning analytics at higher education institutions. · Case studies showcasing successfully implemented learning analytics strategies at higher education institutions. Utilizing Learning Analytics to Support Study Success ably exemplifies how educational data and innovative digital technologies contribute to successful learning and teaching scenarios and provides critical insight to researchers, graduate students, teachers, and administrators in the general areas of education, educational psychology, academic and organizational development, and instructional technology.

Early Warning Systems and Targeted Interventions for Student Success in Online Courses

Early Warning Systems and Targeted Interventions for Student Success in Online Courses PDF Author: Glick, Danny
Publisher: IGI Global
ISBN: 1799850757
Category : Education
Languages : en
Pages : 374

Book Description
Online learning has increasingly been viewed as a possible way to remove barriers associated with traditional face-to-face teaching, such as overcrowded classrooms and shortage of certified teachers. While online learning has been recognized as a possible approach to deliver more desirable learning outcomes, close to half of online students drop out as a result of student-related, course-related, and out-of-school-related factors (e.g., poor self-regulation; ineffective teacher-student, student-student, and platform-student interactions; low household income). Many educators have expressed concern over students who unexpectedly begin to struggle and appear to fall off track without apparent reason. A well-implemented early warning system, therefore, can help educators identify students at risk of dropping out and assign and monitor interventions to keep them on track for graduation. Despite the popularity of early warning systems, research on their design and implementation is sparse. Early Warning Systems and Targeted Interventions for Student Success in Online Courses is a cutting-edge research publication that examines current theoretical frameworks, research projects, and empirical studies related to the design, implementation, and evaluation of early warning systems and targeted interventions and discusses their implications for policy and practice. Moreover, this book will review common challenges of early warning systems and dashboard design and will explore design principles and data visualization tools to make data more understandable and, therefore, more actionable. Highlighting a range of topics such as curriculum design, game-based learning, and learning support, it is ideal for academicians, policymakers, administrators, researchers, education professionals, instructional designers, data analysts, and students.

Proceedings of the 14th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2022)

Proceedings of the 14th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2022) PDF Author: Ajith Abraham
Publisher: Springer Nature
ISBN: 3031275241
Category : Technology & Engineering
Languages : en
Pages : 931

Book Description
This book highlights the recent research on soft computing, pattern recognition, nature-inspired computing, and their various practical applications. It presents 69 selected papers from the 14th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2022) and 19 papers from the 14th World Congress on Nature and Biologically Inspired Computing (NaBIC 2022), which was held online, from December 14 to 16, 2022. A premier conference in the field of soft computing, artificial intelligence, and machine learning applications, SoCPaR-NaBIC 2022 brought together researchers, engineers, and practitioners whose work involves intelligent systems, network security, and their applications in industry. Including contributions by authors from over 25 countries, the book offers a valuable reference guide for all researchers, students, and practitioners in the fields of computer science and engineering.

Blended Learning Designs in STEM Higher Education

Blended Learning Designs in STEM Higher Education PDF Author: Christopher N. Allan
Publisher: Springer
ISBN: 9811369828
Category : Education
Languages : en
Pages : 363

Book Description
This book offers a set of learning principles to support the design of rich learning experiences in Science, Technology, Engineering and Mathematics (STEM) higher education, including detailed evaluations and discussions for a variety of science subjects. Further, it presents a professional learning framework that can be used to support the implementation of blended learning technologies to increase buy-in from academic staff, to support grass roots initiatives, to develop a sense of community, and to sustain change. The principles developed here will help readers to think about blended learning from a learner’s perspective, put learning first, and develop activities that will help learners achieve better learning outcomes. In addition, the book addresses how to design rich, evidence-based, blended learning experiences that support learning. It demonstrates a range of learning principles in practice, with step-by-step instructions, and includes templates, supporting material, instructions and other resources to help teachers embed and adapt designs in their own subject. Readers will be equipped with an expanded toolkit of resources, designs, ideas and activities that can be directly applied in a variety of subject areas.