Estimating Level of Engagement from Ocular Landmarks

E-learning offers many advantages like being economical, flexible and customizable, but also has challenging aspects such as lack of – social-interaction, which results in contemplation and sense of remoteness. To overcome these and sustain learners’ motivation, various stimuli can be incorporated. Nevertheless, such adjustments initially require an assessment of engagement level. In this respect, we propose estimating engagement level from facial landmarks exploiting the facts that (i) perceptual decoupling is promoted by blinking during mentally demanding tasks; (ii) eye strain increases blinking rate, which also scales with task disengagement; (iii) eye aspect ratio is in close connection with attentional state and (iv) users’ head position is correlated with their level of involvement. Building empirical models of these actions, we devise a probabilistic estimation framework. Our results indicate that high and low levels of engagement are identified with considerable accuracy, whereas medium levels are inherently more challenging, which is also confirmed by inter-rater agreement of expert coders

Learner Engagement in Blended Learning Environments: A Conceptual Framework

Learner engagement correlates with important educational outcomes, including academic achievement and satisfaction.  Although research is already exploring learner engagement in blended contexts, no theoretical framework guides inquiry or practice, and little consistency or specificity exists in engagement definitions and operationalizations.  Developing definitions, models, and measures of the factors that indicate learner engagement is important to establishing whether changes in instructional methods (facilitators) result in improved engagement (measured via indicators).  This article reviews the existing literature on learner engagement and identifies constructs most relevant to learning in general and blended learning in particular.  We present a possible conceptual framework for engagement that includes cognitive and emotional indicators, offering examples of research measuring these engagement indicators in technology-mediated learning contexts.  Finally, we suggest future studies to test the framework, which we believe can support advances in blended learning engagement research that is increasingly real-time, minimally intrusive, and maximally generalizable across subject matter contexts

High School Teachers’ Sense of Efficacy: Traditional Teaching vs. Teaching With a Learning Management System

Teacher efficacy has an impact on how students achieve in the classroom. There is a variety of ways teachers help students learn. For example, the method of traditional instruction includes the use of a textbook and teacher lectures. However, a current trend in education is for schools to use a Learning Management System, like Schoology, to help teachers organize and distribute resources to students. This study will help administrators understand if teachers have a stronger or weaker sense of efficacy through the use of traditional instruction or instruction with the use of Schoology. The study is important because administrators need to understand how the programs they are implementing in schools impact teacher efficacy beliefs. The purpose of this causal comparative study was to employ Bandura’s theory of self-efficacy, to identify if there was a difference in high school teacher efficacy beliefs of those who teach with Schoology in their classrooms and those employ traditional methods. The researcher attained permission from the Superintendent of five school districts and high school teachers were asked to participate in the Teacher Sense of Efficacy Scale (TSES) via email. Participants completed the survey through a link in their email, and the researcher analyzed data using the MANOVA to test if each dependent variable of teacher efficacy differs significantly. The MANOVA determined that there was no significant difference among the groups in terms of their teacher efficacy. Although no significant differences were reported, the research adds to the body of literature since there are very few studies on the impact of an LMS in K-12 education

ONE-TO-ONE IPAD TECHNOLOGY IN THE MIDDLE SCHOOL MATHEMATICS AND SCIENCE CLASSROOMS

Science, technology, engineering, and mathematics (STEM) education has become an emphasized component of PreK-12 education in the United States. The US is struggling to produce enough science, mathematics, and technology experts to meet its national and global needs, and the mean scores of science and mathematics students are not meeting the expected levels desired by our leaders (Hossain & Robinson, 2011). In an effort to improve achievement scores in mathematics and science, school districts must consider many components that can contribute to the development of a classroom where students are engaged and growing academically. Computer technology (CT) for student use is a popular avenue for school districts to pursue in their goal to attain higher achievement. The purpose of this study is to examine the use of iPads in a one-to-one setting, where every student has his own device 24/7, to determine the effects, if any, on academic achievement in the areas of mathematics and science. This comparison study used hierarchical linear modeling (HLM) to examine three middle schools in a private school district. Two of the schools have implemented a one-to-one iPad program with their sixth through eighth grades and the third school uses computers on limited occasions in the classroom and in a computer lab setting. The questions addressed were what effect, if any, do the implementation of a one-to-one iPad program and a teacher’s perception of his use of constructivist teaching strategies have on student academic achievement in the mathematics and science middle school classrooms. The research showed that although the program helped promote the use of constructivist activities through the use of technology, the one-to-one iPad initiative had no effect on academic achievement in the middle school mathematics and science classrooms

Evaluating and Integrating Educational Technology in the Elementary Mathematics Classroom

This study used a meta-analysis to analyze several studies examining the impact of technology in the mathematics classroom in order to investigate the functionality of digital tools, and the integration of those digital tools, that most positively impact student achievement and student engagement. Through a keyword search and exclusion criteria, a systematic collection of relevant articles was compiled and analyzed through a two-tier coding scheme. The analysis determined that professional development opportunities need to be provided before, during, and after integration of technology. In addition, educators and students need time prior to the lesson or unit to become familiar with the digital tool and its available functions. Furthermore, educators need to put pedagogy first in order to align strategies with the appropriate digital tools. Finally, digital tools should be introduced in a blended format, with the teacher as a facilitator and the digital activities connected to the curriculum

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

Η χρήση των Εκπαιδευτικών Ρομπότ ως μέσα εκμάθησης του Προγραμματισμού και ως διδακτικά εργαλεία άλλου γνωστικού αντικειμένου. Εκπαιδευτική παρέμβαση για τη διδασκαλία της Φυσικής με τη χρήση των Ozobot Bit.

Η παρούσα διπλωματική, με τίτλο «Η χρήση των Εκπαιδευτικών Ρομπότ ως μέσα εκμάθησης του Προγραμματισμού και ως διδακτικά εργαλεία άλλου γνωστικού αντικειμένου. Εκπαιδευτική παρέμβαση για τη διδασκαλία της Φυσικής με τη χρήση των Ozobot Βit», έχει ως βασικό στόχο τη διερεύνηση της δυνατότητας ένταξης των εκπαιδευτικών ρομπότ σε τυπικά δημόσια δημοτικά σχολεία αλλά και την απόδοση των μαθητών σε διαφοροποιημένο διδακτικό/ μαθησιακό πλαίσιο με την ένταξη τεχνολογικών αντικειμένων. Η έρευνα διενεργήθηκε κατά τη διάρκεια του ακαδημαϊκού έτους 2017-2018 με δείγμα 21 μαθητών, Δ’ τάξης, δημόσιου Δημοτικού σχολείου της Αθήνας. Οι μαθητές κλήθηκαν να ασχοληθούν, στα πλαίσια των μαθημάτων της Μελέτης του Περιβάλλοντος και της Ευέλικτης Ζώνης, με φύλλα εργασίας δραστηριοτήτων που αφορούσαν τόσο την εκμάθηση βασικών αρχών του Προγραμματισμού όσο και βασικές έννοιες των Φυσικών Επιστημών μέσω της χρήσης των εκπαιδευτικών ρομπότ Ozobot Bit, εντός πλαισίου ομαδοσυνεργατικής εργασίας. Τα δεδομένα της εργασίας συλλέχθηκαν με τη χρήση ημερολογίων παρατήρησης της ερευνήτριας, φύλλα εργασιών των μαθητών, καθώς και από ηχογραφημένο- μαγνητοσκοπημένο υλικό που συλλέχθηκε από την σχολική αίθουσα κατά τη διάρκεια υλοποίησης της εκπαιδευτικής παρέμβασης. Στα αποτελέσματα της έρευνας συγκαταλέγονται η εξοικείωση των μαθητών με τα εκπαιδευτικά ρομπότ Ozobot Bit, η κατάκτηση βασικών δεξιοτήτων σε απλές εντολές Προγραμματισμού, αλλά και η εκτέλεση συμβολικών πειραμάτων με τη χρήση των εν λόγω εκπαιδευτικών ρομπότ αντί πραγματικών υλικών.This present thesis, entitled "The use of Educational Robots as a means of learning Programming and as a teaching tool of another subject. Educational intervention for the teaching of Physics with the use of Ozobot Bit.", has as its main objective the investigation of the possible integration of educational robots in typical public elementary schools, as well as the performance of students in a differentiated teaching / learning framework with the introduction of technological objects. The survey was conducted during the academic year 2017-2018 on a sample of 21 students, 4th grade of public elementary school in Athens. Students were invited to deal with projects related to both learning the basic principles of Programming and basic concepts of Science by using educational robots Ozobot Bit and working collaboratively, within two different school subjects. Survey data were collected using researchers' observation calendars, students worksheets, as well as recorded material collected in the classroom during the implementation of the educational intervention. The results of the survey include familiarizing students with Ozobot Bit educational robots, acquiring basic skills in simple programming commands, and performing symbolic experiments using these educational robots instead of real materials