ethanporcaro/eric-fulltext-meta huggingface dataset:
Teaching Pre-Service Teachers How to Utilize Web 2.0 Platforms to Support the Educational Needs of Students with Disabilities in General Education Classrooms
Author: Peterson-Ahmad, Maria B.
Date: 2018-00-00
Type: Journal Articles
Subjects: Preservice Teachers,Preservice Teacher Education,Technology Uses in Education,Web 2.0 Technologies,Educational Needs,Student Needs,Disabilities,General Education,Inclusion,Special Education,Individualized Instruction,Social Media,Web Sites,Use Studies,Educational Strategies

It is without question that technology in schools is here to stay. Educators have always been interested in the extent to which technology can be used to transform education and enhance student learning; however, the degree to which it is utilized in teacher preparation programs for pre-service teachers in terms of Web 2.0 use with future students is under debate. Web 2.0 use can be a particularly interesting tool for teachers to use in differentiating instructional strategies for students with disabilities in inclusive settings. Therefore, it is worthwhile for teacher preparation programs to look at how Web 2.0 platforms can further support students in special education in such settings. The following study delineates data from a study of N = 82 pre-service teachers. Throughout the course of this study, all students were administered a pre- and post-survey that asked questions specific to current knowledge of Web 2.0 and the extent to which they thought it could be used in their future teaching practices. In addition, all students completed an assignment within their respective courses that embedded a specific Web 2.0 component. This assignment required pre-service teacher candidates to utilize the Pinterest platform to find and 'pin' educational materials specific to students with whom they will work with in future inclusive classrooms, relative to the various categories of special education.
Quantitative and Qualitative Analysis of the Learning Analytics and Knowledge Conference 2018
Author: Ochoa, Xavier
Date: 2018-00-00
Type: Journal Articles
Subjects: Educational Research,Data Analysis,Conferences (Gatherings),Foreign Countries,Conference Papers,Peer Evaluation,Writing Evaluation,Writing for Publication,Authors,Discourse Analysis,Educational Trends

LAK-18, the 8th International Conference on Learning Analytics and Knowledge, was hosted by the University of Sydney, Australia, from March 5 to 9, 2018. Traditionally, authors of papers that have received high scores through the review process of the conference are invited to extend their paper and submit it for a special issue of this journal. The chairs of LAK-18 have adopted a double-blind review process that has proven useful in maintaining the technical quality of the conference. Papers submitted to the special issue undergo a rigorous review process that is blind only, not double-blind, as a shorter version of the paper has been already published. The theme for LAK-18 was &quot;Towards User-Centred Analytics&quot;. Though several of the papers receiving high scores in the review process explicitly dealt with this issue, it has been decided to devote a complete special issue of the journal to this theme and invite those papers in this special issue to come. Thus, the present special issue LAK-18 covers a broad range of themes, which reflect well the diversity and the vibrancy of the community, but excludes User-Centred Analytics. This editorial describes the story behind this special issue. This story begins with the contributions submitted to the conference and finishes with a short introduction to the papers in this issue. The two first episodes of the story, contribution type and country, include both tracks, research and practitioner. The reminder episodes refer only to the research track.
Scaling Effective Learning Strategies: Retrieval Practice and Long-Term Knowledge Retention in MOOCs
Author: Davis, Dan
Date: 2018-00-00
Type: Journal Articles
Subjects: Learning Strategies,Online Courses,Electronic Learning,Informal Education,Retention (Psychology),Outcomes of Education,Recall (Psychology),College Students,Scores,Control Groups,Experimental Groups,Cues,Evidence Based Practice

Large-scale online learning environments such as MOOCs provide an opportunity to evaluate the efficacy of learning strategies in an informal learning context with a diverse learner population. Here, we evaluate the extent to which retrieval practice -- recognized as one of the most effective learning strategies -- facilitates long-term knowledge retention (and thus learning outcomes) among MOOC learners using an instructional intervention. We observed no effect on learning outcomes and high levels of treatment non-compliance. In addition, we conducted a series of exploratory studies into long-term recall of knowledge acquired in MOOCs. Surprisingly, both passing and non-passing learners scored similarly on a knowledge post-test, retaining approximately two-thirds of what they learned over the long term.
Processing Image to Geographical Information Systems (PI2GIS)--A Learning Tool for QGIS
Author: Correia, Rui
Date: 2018-00-00
Type: Journal Articles
Subjects: Educational Technology,Technology Uses in Education,Geographic Information Systems,Computer Software,Satellites (Aerospace),Foreign Countries,Higher Education

Education, together with science and technology, is the main driver of the progress and transformations of a country. The use of new technologies of learning can be applied to the classroom. Computer learning supports meaningful and long-term learning. Therefore, in the era of digital society and environmental issues, a relevant role is provided by open source software and free data that promote universality of knowledge. Earth observation (EO) data and remote sensing technologies are increasingly used to address the sustainable development goals. An important step for a full exploitation of this technology is to guarantee open software supporting a more universal use. The development of image processing plugins, which are able to be incorporated in Geographical Information System (GIS) software, is one of the strategies used on that front. The necessity of an intuitive and simple application, which allows the students to learn remote sensing, leads us to develop a GIS open source tool, which is integrated in an open source GIS software (QGIS), in order to automatically process and classify remote sensing images from a set of satellite input data. The application was tested in Vila Nova de Gaia municipality (Porto, Portugal) and Aveiro district (Portugal) considering Landsat 8 Operational Land Imager (OLI) data.
Student Ability Best Predicts Final Grade in a College Algebra Course
Author: O'Connell, Kyle A.
Date: 2018-00-00
Type: Journal Articles
Subjects: Mathematics Instruction,Algebra,College Students,College Mathematics,Mathematics Achievement,Success,Student Characteristics,Student Experience,Grade Point Average,Grades (Scholastic),College Credits,Predictor Variables,Study Habits,Assignments,Racial Differences,Online Courses,Conventional Instruction,Gender Differences,Academic Ability

Historical student data can help elucidate the factors that promote student success in mathematics courses. Herein we use both multiple regression and principal component analyses to explore ten years of historical data from over 20,000 students in an introductory college-level Algebra course in an urban American research university with a diverse student population in order to understand the relationship between course success and student performance in previous courses, student demographic background, and time spent on coursework. We find that indicators of students' past performance and experience, including grade-point-average and the number of accumulated credit hours, best predict student success in this course. We also find that overall final grades are representative of the entire course and are not unduly weighted by any one topic. Furthermore, the amount of time spent working on assignments led to improved grade outcomes. With these baseline data, our team plans to design targeted interventions that can increase rates of student success in future courses.
Developing Reflective Skills of Student Teachers in the Virtual Learning Environment
Author: Straková, Zuzana
Date: 2018-00-00
Type: Journal Articles
Subjects: Student Teachers,Reflection,Thinking Skills,Skill Development,Reflective Teaching,Online Courses,Electronic Learning,Microteaching,Methods Courses,Student Teaching,Undergraduate Students,Foreign Countries,Control Groups,Experimental Groups,Peer Evaluation

A technology supported environment in the educational context has been identified as a useful work space with the potential to deepen the learning experience. This study focuses on ways of using it for the development of reflection as a key teaching competence within initial teacher training. It is based on the premise that enriched reflection conducted in a technology supported environment will result in more a specific, more profound and thus deeper learning experience of student teachers. The purpose of this study was to measure the level of depth of the reflection conducted in a regular higher education ELT methodology course after a microteaching session and to compare it with the reflection student teachers provided after their experience had been enriched by other classmates' suggestions within VLE. The study was conducted over 2 semesters and the research sample consisted of 52 undergraduate students. Non-probability sampling was applied, namely convenience sampling. Both qualitative and quantitative methods were used including content analysis and semi-structured focus-group interviews. To increase the internal validity and objectivity in coding the responses and data interpretation multiple researchers were used. The results of the current study suggest that enriched reflection provided student teachers with such a depth of stimuli that their approach towards their own reflection demonstrated a significant difference in comparison with regular reflection conducted in face to face learning.
Taken Together: Conceptualizing Students&apos; Concurrent Course Enrollment across the Post-Secondary Curriculum Using Temporal Analytics
Author: Brown, Michael
Date: 2018-00-00
Type: Journal Articles
Subjects: At Risk Students,Dropout Prevention,Difficulty Level,College Curriculum,Majors (Students),Enrollment,Predictor Variables,Intellectual Disciplines,Time Factors (Learning),Introductory Courses,Computer Science Education,Undergraduate Students

In this study, we develop and test four measures for conceptualizing the potential impact of co-enrollment in different courses on students' changing risk for academic difficulty and recovery from academic difficulty in a focal course. We offer four predictors, two related to instructional complexity and two related to structural complexity (the organization of the curriculum) that highlight different trends in student experience of the focal course. Course difficulty, discipline of major, time in semester, and simultaneous difficulty across courses were all significantly related to entering a moderate and high-risk classification in the early warning system (EWS). Course difficulty, discipline of major, and time in semester were related to exiting academic difficulty classifications. We observe a snowball effect, whereby students who are experiencing difficulty in the focal course are at increased risk of experiencing difficulty in their other courses. Our findings suggest that different metrics may be needed to identify risk for academic difficulty and recovery from academic difficulty. Our results demonstrate what a more holistic assessment of academic functioning might look like in early warning systems and course recommender systems, and suggest that academic planners consider the relationship between course co-enrollment and student academic success.
Learn from Your (Markov) Neighbour: Co-Enrollment, Assortativity, and Grade Prediction in Undergraduate Courses
Author: Gardner, Josh
Date: 2018-00-00
Type: Journal Articles
Subjects: Markov Processes,Classification,Undergraduate Students,Grade Point Average,State Universities,Longitudinal Studies,Networks,Predictor Variables,Comparative Analysis,Academic Achievement,Models,Enrollment,Network Analysis

In this paper, we evaluate the complete undergraduate co-enrollment network over a decade of education at a large American public university. We provide descriptive and exploratory analyses of the network, demonstrating that the co-enrollment networks evaluated follow power-law degree distributions similar to many other large-scale networks; that they reveal strong performance-based assortativity; and that network-based features can improve GPA-based student performance predictors. We model the university-wide undergraduate co-enrollment network as an undirected graph, and implement multiple network-augmented approaches to student grade prediction, including an adaption of the structural modelling approach from (Getoor, 2005; Lu &amp; Getoor, 2003a). We compare the performance of this predictor to traditional methods used for grade prediction in undergraduate university courses, and demonstrate that a multi-view ensembling approach outperforms both prior &quot;flat&quot; and network-based models for grade prediction across several classification metrics. These findings demonstrate the usefulness of combining diverse approaches in models of student success, and demonstrate specific network-based modelling strategies that are likely to be most effective for grade prediction.
The SHEILA Framework: Informing Institutional Strategies and Policy Processes of Learning Analytics
Author: Tsai, Yi-Shan
Date: 2018-00-00
Type: Journal Articles
Subjects: Data Analysis,Learning,Educational Policy,Higher Education,Strategic Planning,Adoption (Ideas),Models,Policy Formation,Foreign Countries

This paper introduces a learning analytics policy and strategy framework developed by a cross-European research project team -- SHEILA (Supporting Higher Education to Integrate Learning Analytics), based on interviews with 78 senior managers from 51 European higher education institutions across 16 countries. The framework was developed adapting the RAPID Outcome Mapping Approach (ROMA), which is designed to develop effective strategies and evidence-based policy in complex environments. This paper presents four case studies to illustrate the development process of the SHEILA framework and how it can be used iteratively to inform strategic planning and policy processes in real world environments, particularly for large-scale implementation in higher education contexts. To this end, the selected cases were analyzed at two stages, each a year apart, to investigate the progression of adoption approaches that were followed to solve existing challenges, and identify new challenges that could be addressed by following the SHEILA framework.
Topic Dependency Models: Graph-Based Visual Analytics for Communicating Assessment Data
Author: Khosravi, Hassan
Date: 2018-00-00
Type: Journal Articles
Subjects: Graphs,Academic Achievement,Student Evaluation,Models,Statistical Analysis,Computer Science Education,Undergraduate Students

Educational environments continue to evolve rapidly to address the needs of diverse, growing student populations while embracing advances in pedagogy and technology. In this changing landscape, ensuring consistency among the assessments for different offerings of a course (within or across terms), providing meaningful feedback about student achievements, and tracking student progress over time are all challenging tasks, particularly at scale. Here, a collection of visual Topic Dependency Models (TDMs) is proposed to help address these challenges. It uses statistical models to determine and visualize student achievements on one or more topics and their dependencies at a course level reference TDM (e.g., CS 100) as well as assessment data at the classroom level (e.g., students in CS 100 Term 1 2016 Section 001), both at one point in time (static) and over time (dynamic). The collection of TDMs share a common two-weighted graph foundation. Exemplar algorithms are presented for the creation of the course reference and selected class (static and dynamic) TDMs; the algorithms are illustrated using a common symbolic example. Studies on the application of the TDM collection on datasets from two university courses are presented; these case studies utilize the open-source, proof of concept tool under development.
Using Temporal Analytics to Detect Inconsistencies between Learning Design and Student Behaviours
Author: Nguyen, Quan
Date: 2018-00-00
Type: Journal Articles
Subjects: Time Management,Online Courses,Educational Technology,Technology Uses in Education,Instructional Design,Assignments,Teaching Methods,Context Effect,Data Collection,Data Analysis,Foreign Countries,Distance Education,Integrated Learning Systems,College Students,Environmental Education

Extensive research in learning science has established the importance of time management in online learning. Recently, learning analytics (LA) has shed further lights on the temporal characteristics of learning by allowing researchers to capture authentic digital footprints of student learning behaviours. Nonetheless, students' timing of engagement and its relation to learning design (LD) and academic performance have received limited attention. This study investigates to what extent students' timing of engagement aligned with instructor learning design, and how engagement varied across different levels of performance. Our findings revealed a mismatch between how instructors designed for learning and how students study. In most weeks, students spent less time studying the assigned materials on the virtual learning environment (VLE) compared to the number of hours recommended by instructors. The timing of engagement also varied, from in advance to catching up patterns. High-performing students spent more time studying in advance, while low-performing students spent a higher proportion of their time on catching-up activities. By incorporating the pedagogical context into learning analytics, not only we can understand what, why, and when students engage, but also how their behaviours are influenced by the way instructors design for learning.
What Constitutes an &quot;Actionable Insight&quot; in Learning Analytics?
Author: Jørnø, Rasmus Leth
Date: 2018-00-00
Type: Journal Articles
Subjects: Data Analysis,Learning,Educational Research,Definitions,Data,Decision Making

The possibilities of Learning Analytics as a tool for empowering teachers and educators have created a steep interest in how to provide so-called actionable insights. However, the literature offers little in the way of defining or discussing what the term &quot;actionable insight&quot; means. This selective literature review provides a look into the use of the term in current literature. The review points to a dominant perspective in the literature that assumes the perspective of a rational actor, where actionable insights are treated as insights mined from data and subsequently acted upon. It also finds evidence of other perspectives and discusses the need for clarification of the term in order to establish a more precise and fruitful use of the term.
University Engagement in Achieving Sustainable Development Goals: A Synthesis of Case Studies from the SUEUAA Study
Author: Neary, Joanne
Date: 2018-11-00
Type: Journal Articles
Subjects: Case Studies,Sustainable Development,Foreign Countries,Community Involvement,Universities,Partnerships in Education,Municipalities,Institutional Mission,School Community Relationship,Poverty

While initial discussions of the third mission of universities focussed on market-orientated behaviours of universities, more recently it has been connected to activities that focus on social justice and promoting sustainability (Trencher, Bai, Evans, McCormick &amp; Yarime, 2014; Appe &amp; Barragán, 2017). It has been suggested that the third mission of universities in the Global South may be particularly significant in addressing acutely felt issues of climate change, economic inequalities, food insecurity and urban sprawl. The current paper explores this and asks whether the quadruple helix (Carayannis &amp; Campbell, 2010) is visible in their engagement activities. Using a synthesis of case studies developed as part of the 'Strengthening Urban Engagement of Universities in Africa and Asia' (SUEUAA) project, a collaborative research project spanning seven cities (Glasgow; Harare; Dar-es-Salaam; Johannesburg; Duhok; Sanandaj; and Manila), we explore ongoing engagement activities where universities respond to city demand. We frame this in terms of Sustainable Development Goals. Results indicate while universities were seen to address city demands, they often reacted without a network of other influential actors (i.e. industry, local government or NGO partners). This suggests that currently, the quadruple helix is underdeveloped in these cities, and more work should be done in creating closer links.
To Understand the &quot;Brazilian Way&quot; of School Management: How National Culture Influences the Organizational Culture and School Leadership
Author: Moreira, Ana Maria de Albuquerque
Date: 2018-00-00
Type: Journal Articles
Subjects: Foreign Countries,Cultural Influences,Organizational Culture,Leadership Effectiveness,Instructional Effectiveness,School Administration

This study aims to identify characteristics of national culture in the culture of Brazilian school management and leadership. Considering the broad literature that deals with the peculiarities of Brazilian culture and its influence on Brazilian management, it is assumed that as an institution belonging to a particular society, the school offers internal dynamics that are organized under influences of historical and cultural determinants of this society. This work is an exploratory study that uses secondary data found in studies on the profiles of principals, leadership, climate, and organizational culture in schools and primary data from research applied in public secondary schools located in the Federal District, Brazil. The results demonstrate that the initial premise--national culture influences the organizational culture and school leadership--has been confirmed and aspects that merit further analysis are identified.