ethanporcaro/eric-fulltext-meta huggingface dataset:
Motivation Heightens and Independent Thinking Deepens: Undergraduate Students Share Their Experiences of PBL While Learning Microeconomics
Author: Dookwah, Rhonda
Date: 2022-08-00
Type: Journal Articles
Subjects: Student Motivation,Thinking Skills,Undergraduate Students,Problem Based Learning,Student Experience,Student Attitudes,Microeconomics,Foreign Countries

The aim of this study is to analyze the use of Problem-Based Learning (PBL) in learning Microeconomics. It aims to answer the following research questions: What are the experiences of undergraduate students who studied with Problem-Based Learning (PBL)? Is this strategy useful at the undergraduate level? Does PBL really motivate students? Does it foster independent thinking? These questions are interesting but very complex and convoluted. The above questions created parameters for this action research which was done in relation to the teaching of an undergraduate course at a tertiary education institution. This paper presents the experiences of sixteen undergraduates at a tertiary institution in Trinidad and Tobago called New Model University. There is a paucity of information in the local setting as it pertains to this topic. As a result, the experiences of these sixteen students are valuable. Their diverse voices and varied experiences can certainly fill the existing gap. They can be instrumental for the better creation of policy. They can also assist in the effective implementation of PBL at tertiary education in Trinidad and Tobago. Furthermore, their voices and opinions answer the research question: What are the experiences of students who use Problem-Based Learning in the study of Microeconomics at New Model University? A seven-step approach to PBL was utilized as the main teaching and learning process. A case study was conducted over a period of twelve weeks. It incorporated open-ended questions and semi-structured interviews with four focus groups. The individual reflections and independent experiences of these sixteen students were carefully documented in weekly journals, and this complemented the data collection process. Data were collected, collated, analyzed, and narrated using six major themes. Recommendations which strongly advocate student-centered strategies were offered.
The Effect of Education Groups on the Quality of Urban and Rural Compulsory Education: An Empirical Analysis Based on CEPS Data
Author: Cheng, Gang
Date: 2022-00-00
Type: Journal Articles
Subjects: Foreign Countries,Compulsory Education,Urban Schools,Rural Schools,Rural Urban Differences,Educational Quality,Cognitive Ability,Educational Cooperation

We retrieved data from China Education Panel Survey (CEPS) and adopted the hierarchical linear model as well as the quantile regression method to examine the effect of education groups on the quality of urban and rural compulsory education. Student cognitive ability was cited as the evaluation index of education quality. According to the research findings, the overall effect of education groups on the quality of compulsory education is significantly positive, but there is urban-rural heterogeneity in this effect: the positive impact occurs only to urban member schools, while the education quality of rural member schools has not been improved by school grouping. In addition, there exists individual difference in this effect; school grouping significantly and negatively affects students from rural member schools and with medium and lower cognitive ability.
An Empirical Study on the Data Analytics-Based Self-Regulated Learning Scaffolding Model for Primary Students
Author: Wang, Han
Date: 2022-00-00
Type: Journal Articles
Subjects: Elementary School Students,Scaffolding (Teaching Technique),Learning Strategies,Models,Foreign Countries,Learning Analytics,Outcomes of Education,Metacognition,Student Attitudes,Student Characteristics

In the age of Internet Plus, the deep integration of information technology into education and individualized instruction have become a growing trend in education development. Self-regulated learning is a key element of student core competence, but easy to be overlooked in basic education. The purpose of this study is to establish the data analytics-based self-regulated learning scaffolding model for primary students and test its results in teaching practice, citing Scaffolding Theory and Zone of Proximal Development Theory as its rationale. Research findings demonstrate that learning data analytics-enabled self-regulated after-class learning can help enhance learning outcomes and develop student learning strategies.
Factors Influencing the Turnover Intention of Rural Preschool Teachers in the Context of Rural Revitalization: An Analysis Based on a Moderated Mediation Model
Author: Wang, Tao
Date: 2022-00-00
Type: Journal Articles
Subjects: Preschool Education,Rural Schools,Teacher Persistence,Preschool Teachers,Teacher Attitudes,Anxiety,Faculty Mobility,Intention,Work Attitudes,Foreign Countries

The retention of teachers is critical to the development of rural preschool education in China. We conducted a sample survey of 3790 rural kindergarten teachers from 22 counties (or cities) of 10 provinces and examined the effects of work stress and job apathy on the turnover intention of rural preschool teachers using the work stress, job apathy and turnover intention scales. According to the research findings, work stress can significantly predict rural kindergarten teachers' turnover intention; job apathy plays a mediating role between job stress and teacher turnover intention, and the indirect effect is greater than the direct effect; Bianzhi membership can moderate the direct effect of work stress on teacher turnover intention and the mediating effect of job apathy.
Online Shadow Education in Hong Kong: Perspectives from Secondary School Students and Private Tutors
Author: Cheng, Ching Ho
Date: 2022-00-00
Type: Journal Articles
Subjects: Tutoring,Private Education,Secondary School Students,Student Attitudes,Electronic Learning,Tutors,Attitudes,Educational Technology,Foreign Countries,Educational Trends,Futures (of Society)

Based on the educational hierarchical reproduction theory and the MMI and EMI hypotheses, this paper discusses the impact of the tracking of general and vocational education at the secondary level on higher education opportunity equity among social classes. The study finds that increasing gross enrollment rates of both general high schools and secondary vocational schools can help improve the equity in admission opportunities of colleges and universities among social strata; expanding the share of general high school places by adjusting the structure of general and vocational tracks (that is, the general-vocational ratio) can effectively reduce the class disparities in college and university admission opportunities; neither the change in the scale nor in the structure of general and vocational tracks will contribute to alleviating class inequality in top university enrollment opportunities.
The Effect of School Organizational Support on Job Satisfaction of Primary and Secondary School Teachers: The Mediating Role of Teachers&apos; Engagement in Educational Research
Author: Wang, Weihao
Date: 2022-00-00
Type: Journal Articles
Subjects: Job Satisfaction,Elementary School Teachers,Secondary School Teachers,School Support,Educational Research,Teacher Participation,Foreign Countries,Teacher Attitudes

The topic of teacher work satisfaction has long been a focus of educational study. This study examined the impact of school organizational support on teacher job satisfaction as mediated by teachers' engagement in educational research, utilizing the findings of a survey on the academic quality of basic education students in Jiangsu Province in 2020 and analyzing the data of 21,154 primary and 16,585 secondary school teachers. In this work, the structural equation model is utilized. Significant favorable relationships are shown between school organization support, teachers' participation in educational research, and teachers' work happiness. The engagement of teachers in educational research somewhat mediates the relationship between school organization support and teacher job happiness. School organization support positively predicts teacher job satisfaction. The impact of school organization support on teachers' participation in educational research and job satisfaction is greater at the primary level than at the junior secondary level.
Impact of COVID-19-Related Distress on Anxiety and Depression of College Students
Author: Mathew, Jain
Date: 2022-00-00
Type: Journal Articles
Subjects: COVID-19,Pandemics,Anxiety,Depression (Psychology),College Students,Mental Health,Well Being,Foreign Countries

The current study explores the impact of COVID-19 related distress factors on the mental wellbeing of college students. For the purpose of the study, mental well-being is measured through the depression symptoms and general anxiety levels of the students. The study used judgemental sampling to identify the respondents of the study. The final sample consisted of 147 respondents and the data was analysed on SPSS. The results suggested that while COVID-19 distress factors were not significant in predicting the level of depression symptoms experienced by the students, the general anxiety levels were significantly impacted by the distress factors. The findings are particularly useful for the teachers and institutions working to connect and teach through online platforms.
Innovative Open Schooling in Secondary Education in Mozambique: Technological Conditions for Students to Attend Distance Learning
Author: Cossa, Sérgio Paulo
Date: 2022-00-00
Type: Journal Articles
Subjects: Foreign Countries,Access to Education,Distance Education,Open Education,Secondary School Students,Student Participation,Educational Technology,Readiness,Training,Access to Computers,Computers,Handheld Devices,Internet,Technological Literacy

This article describes part of the results, taken from ongoing initial research, on the potential of new media in distance education. The article explores the technological conditions that students involved in Open and Innovative Schooling (OIS) experience, focusing on the fifteen schools in Mozambique. Participants were selected by intentional sampling and a mixed method research approach was then followed. The results revealed that, in general, minimum technological conditions were created at schools for the distance learning process, despite some asymmetries between schools and students. These findings are useful for documenting and sharing the real condition under which OIS operates in the Mozambican context. Furthermore, it is key to influencing educational policies in order to include training in digital literacy, as well as strategies for technology distribution for students from the mentioned schools. These are also crucial for an in-depth reflection on the aspects to be improved for a better implementation of OIS.
University-Wide Assessment during COVID-19: An Opportunity for Innovation
Author: Pastor, Dena
Date: 2020-00-00
Type: Journal Articles
Subjects: Student Evaluation,COVID-19,Pandemics,Evaluation Methods,Educational Innovation,Outcomes of Education,College Students,Distance Education,Computer Assisted Testing

For more than 30 years, James Madison University (JMU) has used Assessment Days to collect longitudinal data on student learning outcomes. Our model ensures that all incoming students are tested twice: once in August before beginning classes and again in February after accumulating 45-70 credit hours (Pastor, Foelber, Jacovidis, Fulcher &amp; Love, 2019). Although a student completes only four instruments each Assessment Day, 25 different assessments are administered, thereby allowing for the examination of student growth on a variety of different outcomes. Various changes have been made to Assessment Day throughout the years, but none as dramatic as those we are making to the August 2020 Assessment Day in response to the COVID-19 pandemic.
Considerations for Meaningful Assessment during COVID-19
Author: Harrison, Laura M.
Date: 2020-00-00
Type: Journal Articles
Subjects: Student Evaluation,COVID-19,Pandemics,Evaluation Methods,Equal Education,Interviews,College Students

COVID-19 presents assessment professionals with an opportunity to reexamine preexisting inequities for vulnerable student groups that may be more susceptible to the pandemic's economic impacts. We propose that assessment professionals incorporate student interviews more intentionally in their work so they and their stakeholders can develop more meaningful understandings of these inequities, provide a higher degree of contact with students, and appreciate better how policies enacted during the pandemic may impact students.
Quarantining High-Stakes Assessments in an Introductory Physics Class
Author: Pearson, Richard L., III
Date: 2020-00-00
Type: Journal Articles
Subjects: High Stakes Tests,Introductory Courses,Physics,COVID-19,Pandemics,Distance Education,Electronic Learning,Evaluation Methods

In the Spring of 2020, Embry-Riddle Aeronautical University (ERAU) physics faculty used the rapid response and change of teaching modality to the pandemic to holistically re-imagine the course assessments. They developed and implemented a course architecture that focused on more smaller-stakes assessments to better engage students with the learning process. Those changes will remain in the introductory physics course moving forward.
Leading with Empathy and Learning to Flex
Author: Soto, Eileen
Date: 2020-00-00
Type: Journal Articles
Subjects: Educational Administration,Empathy,COVID-19,Pandemics,Leadership Styles,Program Administration,Program Evaluation,Evaluation Methods,School Closing,College Administration,Teamwork

When instruction shifted online as a result of COVID-19 in March 2020, Educational Effectiveness staff considered how best to serve our institution with available resources, skills, and services, while maintaining ongoing assessment. Administration of program-level assessment activities, such as overseeing the completion of program reviews, planning for upcoming program reviews, and advising faculty on annual program learning outcome assessment were opportunities to lead with increased empathy and flexibility. The unfamiliar nature of operating in the midst of a pandemic also required fresh data from students, faculty, and staff. Empathy and timeliness in our communications were essential in supporting our institution.
The Value of a Curriculum Map to Minimize Harm from Emergency Remote Instruction
Author: Singer-Freeman, Karen
Date: 2020-00-00
Type: Journal Articles
Subjects: Emergency Programs,Electronic Learning,Distance Education,COVID-19,Pandemics,Curriculum,Concept Mapping,Academic Achievement,Educational Benefits,Higher Education,Achievement Gap

The academic disruption initiated by the COVID-19 pandemic created a need for faculty to examine students' continuity of learning. As current assessment professionals and former faculty members, we recognize this as an opportunity to utilize curriculum maps as tools to identify and address possible learning gaps that may have occurred. The intended audience for this article includes faculty considering ways to ensure continuity of learning during academic disruption and assessment professionals working with faculty to develop and make use of curriculum maps.
A Learning Analytics Approach to Monitoring the Quality of Online One-to-One Tutoring
Author: Cukurova, Mutlu
Date: 2022-00-00
Type: Journal Articles
Subjects: Learning Analytics,Tutoring,Educational Quality,Behavior Patterns,Computer Software,Mathematics Instruction,Elementary School Students,Decision Making,Teacher Behavior,Accuracy,Teacher Effectiveness,Tutors,Lesson Plans,Computer Assisted Instruction

One-to-one online tutoring provided by human tutors can improve students' learning outcomes. However, monitoring the quality of such tutoring is a significant challenge. In this paper, we propose a learning analytics approach to monitoring online one-to-one tutoring quality. The approach analyzes teacher behaviours and classifies tutoring sessions into those that are effective and those that are not effective. More specifically, we use sequential behaviour pattern mining to analyze tutoring sessions using the CM-SPAM algorithm and classify tutoring sessions into effective and less effective using the J-48 and JRIP decision tree classifiers. To show the feasibility of the approach, we analyzed data from 2,250 minutes of online one-to-one primary math tutoring sessions with 44 tutors from eight schools. The results showed that the approach can classify tutors' effectiveness with high accuracy (F measures of 0.89 and 0.98 were achieved). The results also showed that effective tutors present significantly more frequent hint provision and proactive planning behaviours than their less-effective colleagues in these online one-to-one sessions. Furthermore, effective tutors sequence their monitoring actions with appropriate pauses and initiations of students' self-correction behaviours. We conclude that the proposed approach is feasible for monitoring the quality of online one-to-one primary math tutoring sessions.
Curriculum Modelling and Learner Simulation as a Tool in Curriculum (Re)Design
Author: McEneaney, John
Date: 2022-00-00
Type: Journal Articles
Subjects: Curriculum Design,Learning Analytics,Educational Change,Computer Software,Computer Simulation,Models,Student Characteristics,College Students,Generalization

Learning analytics (LA) provides tools to analyze historical data with the goal of better understanding how curricular structures and features have impacted student learning. Forward-looking curriculum design, however, frequently involves a degree of uncertainty. Historical data may be unavailable, a contemplated modification to curriculum may be unprecedented, or we may lack data regarding particular learner populations. To address this need, we propose using curriculum modelling and learner simulation (CMLS), which relies on well-established modelling theory and software to represent an existing or contemplated curriculum. The resulting model incorporates relevant research-based principles of learning to individually simulate learners and estimate their learning achievement as they move through the modelled curriculum. Results reflect both features of the curriculum (e.g., time allocated to different learning outcomes), learner profiles, and the natural variability of learners. We describe simulations with two versions of a college-level curriculum, explaining how results from simulations informed curriculum redesign work. We conclude with commentary on generalizing these methods, noting both theoretical and practical benefits of CMLS for curriculum (re)design.
Developing a Code of Practice for Using Data in Wellbeing Support
Author: Cormack, Andrew
Date: 2022-00-00
Type: Journal Articles
Subjects: Foreign Countries,Well Being,Data Use,Ethics,Learning Analytics,Information Policy,Privacy,Standard Setting

With student and staff wellbeing a growing concern, several authors have asked whether existing data might help institutions provide better support. By analogy with the established field of Learning Analytics, this might involve identifying causes of stress, improving access to information for those who need it, suggesting options, providing rapid feedback, even early warning of problems. But just investigating the possibility of such uses can create significant risks for individuals: feelings of creepiness or surveillance making wellbeing worse, inappropriate data visibility destroying trust, assessments or interventions becoming self-fulfilling prophecies. To help institutions decide whether and how to explore this area, and to reassure individuals that this is being done safely, we propose a Wellbeing Analytics Code of Practice. This starts from an existing Learning Analytics Code, confirms that its concerns and mitigations remain relevant, and adds additional safeguards and tools for the wellbeing context. These are derived from a detailed analysis of European and UK data protection law, extracting all rules and safeguards mentioned in relation to health data. We also develop context-specific tools for managing risk and evaluating data sources. Early feedback suggests that these documents will indeed increase confidence that this important area can be safely explored.
Designing Affirmative Action Policies under Uncertainty
Author: Hertweck, Corinna
Date: 2022-00-00
Type: Journal Articles
Subjects: Affirmative Action,Policy Formation,Educational Policy,College Admission,Policy Analysis,Prediction,Artificial Intelligence,Social Justice,Data Use,Foreign Countries,Social Differences

We study university admissions under a centralized system that uses grades and standardized test scores to match applicants to university programs. In the context of this system, we explore affirmative action policies that seek to narrow the gap between the admission rates of different socio-demographic groups while still accepting students with high scores. Since there is uncertainty about the score distribution of the students who will apply to each program, it is unclear what policy would have the desired effect on the admission rates of different groups. We address this challenge by using a predictive model trained on historical data to help optimize the parameters of such policies. We find that a learned predictive model does significantly better than relying on the ideal parameters for the last year. At the same time, we also find that a large pool of historical data yields similar results as our predictive approach for our data. Due to the more complex nature of the predictive approach, we conclude that a simpler approach should be preferred if enough data is available (e.g., long-standing, traditional university programs), but not for newer programs and other cases in which our predictive strategy can prove helpful.
Developing a Growth Learning Data Mindset: A Secondary School Approach to Creating a Culture of Data Driven Improvement
Author: Vigentini, Lorenzo
Date: 2022-00-00
Type: Journal Articles
Subjects: Learning Analytics,Educational Improvement,Secondary School Students,Learning Management Systems,Governance,Educational Practices,Evaluation Methods,Student Improvement,Private Schools,Evidence,Educational Policy,Educational Administration,Learning Processes,Metacognition,Foreign Countries

While Learning Analytics (LA) have gained momentum in higher education, there are still few examples of application in the school sector. Even fewer cases are reported of systematic, organizational adoption to drive the support of student learning trajectories that includes teachers, pastoral leaders, and academic managers. This paper presents one such case -- at the intersection of praxis, governance, and evaluation -- from a practitioner perspective. The paper describes the added value of data-driven approaches to create a culture of improvement in students and teachers in a comprehensive coeducational independent day school in Sydney. Evaluating the work done over the past five years to develop LA dashboards, the authors reflect on the process, the inspirations coming from theory, and the impact of the dashboards in the secondary school context. The data presented is not experimental in nature but supplies tangible evidence for the systematic evaluation scaffolded using the SHEILA policy framework. The main contribution of the paper is a practical demonstration of how managers in a secondary school drew from existing literature and observed data to 1) reflect on the adoption of LA in schools and 2) connect the dots between theory and practice to support teachers grappling with the trajectories of student learning and development, thus encouraging students to self-regulate their learning.