ethanporcaro/eric-fulltext-meta huggingface dataset:
Understanding Elementary and Middle School Counselors&apos; Experiences with Disability Awareness and Advocacy
Author: Bialka, Christa S.
Date: 2020-00-00
Type: Journal Articles
Subjects: Students with Disabilities,Middle Schools,School Counselors,Advocacy,Consciousness Raising,Attitudes toward Disabilities,At Risk Students,Social Justice,Counselor Training,Counselor Role,Social Bias,Elementary Schools,Student Empowerment,Student Needs

Students with disabilities are at greater risk for depression, substance use, bullying, and fewer friendships, largely due to negative attitudes and misperceptions from their nondisabled peers. School counselors are particularly important stakeholders in improving the experiences of students with disabilities. This qualitative study uses the American Counseling Association (ACA) Advocacy Competencies as a lens to understand how six school counselors raise disability awareness within the context of social justice advocacy. Results indicate that participants primarily focused on ways to advocate alongside or on behalf of students with disabilities at an individual level (client/student domain). Additional findings highlight the need for increased disability-related training within counselor preparation programs and the importance of including disability issues within the frame of multicultural competence. The results of this study fill a gap in the literature and lead to a deeper understanding of how school counselors are presently engaging in disability programs in their schools. Additionally, findings from this research directly aid in the construction of coursework and related experiences that would enhance the preparation of pre-service school counselors.
Civil Law Agreement and Its Implication on Regulation for Prevention of Corruption within COVID-19 Pandemic
Author: Hamzah
Date: 2020-00-00
Type: Journal Articles
Subjects: Laws,Prevention,Federal Regulation,Contracts,Deception,Social Problems,Expenditures,COVID-19,Pandemics,Foreign Countries,Trust (Psychology),Crime,Ethics

The purpose of this study is to determine the social impact of the learning process of agreements and regulations in the Civil Law regarding the procurement of goods and services during the COVID-19 pandemic, its implications for preventing corruption in Indonesia. The research method used is normative using a theory-in-use approach. The results of the study found three crucial points. First, the law of goods and services agreements gives freedom to people who do not have restrictions in the code for that. The contract for the procurement of products and services during the COVID-19 pandemic was categorized as a relatively temporary force majeure so that it could renegotiate to rearrange the implementation schedule. Second, good faith is the key to success in resolving frustrating agreement problems to save the agreement to provide benefits and benefits to both parties. Third, in the end, civil law provides an essential lesson that in transactions based on good faith where there are values of decency, honesty, and fair wisdom is the prevention of corruption in the procurement of goods. Good faith is the key to success in resolving frustrating agreement problems to save the agreement to provide benefits and benefits to both parties. And service in difficult times like today.
Exploring Religious Teaching and Attitudes of Traditional Muslim on Social Politics in Indonesia
Author: Situmorang, Jubair
Date: 2020-00-00
Type: Journal Articles
Subjects: Religious Education,Teaching Methods,Muslims,Foreign Countries,Citizen Participation,Political Attitudes,Social Adjustment,Ethics,Phenomenology,Religious Factors,Islam,Social Attitudes,Politics,Democratic Values,Justice,Prosocial Behavior,Intergroup Relations,Social Responsibility,Civil Rights,Spiritual Development

Today Indonesia encounters a significant downturn in its political life amid the society participation, among other things, by traditional Muslim society. Consequently, attentions are drawn to the religious teaching the traditional Muslims obtain to adapt to social or political life in Indonesia. This study aims to describe the impact of religious teaching on traditional Muslims' ethical behaviors and to analyze their behavior shifts towards the socio-political situations in Indonesia. A literature review was employed as the data collection technique by way of observations, in-depth interviews and documentaries. Semi-structured interviews were selected using purposive sampling techniques. The population and participants involved came from the Ternate Sultanate, North Maluku Province, Indonesia. The research methodology used the historical, sociological, theological and phenomenological approaches to analyze problems related to traditional Muslim political life and the role of religious teachings in it. The result demonstrated that the traditional Muslims, who appeared to be rigid, doctrinal, and intolerant towards newly developed ideas, were influenced by literal perceptions. Furthermore, strong local cultures and attitudes performed in religious rituals for maintaining traditions over generations have also created the various attitudes of traditional Muslims towards the politics in Indonesia. The interviews revealed that the existence of &quot;'Pangaji'&quot; (a term for religious leaders who teach religious teaching in the Sultanate of Ternate) in &quot;'Bobato'&quot; could shape improved individual characteristics. Based on the diversity paradigm approach, &quot;'Pangaji',&quot; despite their rarity in modern Muslim societies, has resulted in a shift in political behaviors wherein democratic values, justice, solidarity among society groups, a sense of responsibility, and respect for human rights are promoted. This finding hopefully strengthens the political structure in Indonesia, as the existence of religious teaching should initiate spiritual expansion, which seeks to help the Muslim society understand the true meaning and function of religious and socio-political life.
Stability and Predictors of Students&apos; Treatment Acceptability of Check &amp; Connect across Time
Author: Tsai, Shu-Chen
Date: 2020-12-00
Type: Journal Articles
Subjects: Intervention,High School Students,Behavior Disorders,Emotional Disturbances,Student Attitudes,Predictor Variables,Reliability,Mentors,Learner Engagement

Student views of treatment acceptability of an intervention is important but still is neither regularly assessed nor studied beyond non-behavioral interventions. Furthermore, assessment of treatment acceptability across time is almost never considered. Using data from a longitudinal, randomized controlled trial, we examined variables that predicted students' treatment acceptability of Check &amp; Connect, a mentoring intervention with promise for promoting school engagement. A series of multiple regressions with multiple imputations revealed that students' treatment acceptability ratings in Year 1 significantly predicted Year 2 ratings. Other variables examined, including dosage, change in mentor, and student and mentor characteristics, were not significant in predicting students' treatment acceptability ratings in Year 2. Implications for using treatment acceptability to facilitate buy-in and further replications are discussed.
Analytics of Learning Strategies: Role of Course Design and Delivery Modality
Author: Matcha, Wannisa
Date: 2020-00-00
Type: Journal Articles
Subjects: Learning Analytics,Learning Strategies,Instructional Design,Delivery Systems,Learning Modalities,Generalizability Theory,Flipped Classroom,Open Education,Online Courses,Context Effect,Academic Achievement,Correlation,Self Management,Problem Solving,Computer Science Education,Science Education,College Freshmen,Foreign Countries

Generalizability of the value of methods based on learning analytics remains one of the big challenges in the field of learning analytics. One approach to testing generalizability of a method is to apply it consistently in different learning contexts. This study extends a previously published work by examining the generalizability of a learning analytics method proposed for detecting learning tactics and strategies from trace data. The method was applied to the datasets collected in three different course designs and delivery modalities, including flipped classroom, blended learning, and massive open online course. The proposed method combines process mining and sequence analysis. The detected learning strategies are explored in terms of their association with academic performance. The results indicate the applicability of the proposed method across different learning contexts. Moreover, the findings contribute to the understanding of the learning tactics and strategies identified in the trace data: learning tactics proved to be responsive to the course design, whereas learning strategies were found to be more sensitive to the delivery modalities than to the course design. These findings, well aligned with self-regulated learning theory, highlight the association of learning contexts with the choice of learning tactics and strategies.
Using Positive Behavioral Interventions and Supports to Reduce School Suspensions
Author: Gage, Nicholas A.
Date: 2020-12-00
Type: Journal Articles
Subjects: Student Behavior,Behavior Problems,Positive Behavior Supports,Intervention,Suspension,Discipline,Emotional Disturbances,Behavior Disorders,Expectation,Holistic Approach,Positive Reinforcement,Data Collection,Feedback (Response),Program Implementation,Classroom Techniques

The Positive Behavioral Interventions and Supports (PBIS) framework is currently implemented in more than 25,000 schools across the globe. Its implementation has demonstrated positive impacts on a number of behavioral and academic outcomes. A growing evidence base has found that PBIS has been particularly effective at reducing both in- and out-of-school suspensions. This article describes concerns with the use of suspensions, defines PBIS, and outlines how schools can implement and use PBIS to reduce suspensions.
National Universities in Argentina during the Pandemic Outbreak
Author: Mendonça, Mariana
Date: 2020-00-00
Type: Journal Articles
Subjects: Foreign Countries,Universities,Educational Change,COVID-19,Pandemics,Electronic Learning,Web Based Instruction,Decision Making,Online Courses,Distance Education,College Role,Public Health,Diagnostic Tests,Scientific Research,Immunization Programs

Background: The health emergency that Argentina is experiencing because of the COVID-19 pandemic radically changed institutional normality at all educational levels. Universities have certainly not escaped this logic. Whilst their first response was a general shut down, along with a shift to online teaching and learning, the actions taken in response to the pandemic went far and beyond. These institutions sought to contribute, in different ways, to satisfy the new social demands linked to the outbreak of the health emergency. Aim: We aim to give an account of the actions that the national universities in Argentina took in response to the distinctive social demands linked to the pandemic outbreak. Setting: Specifically, we focused on the academic and pedagogical decisions, the reorientation of scientific research, the availability of infrastructure and resources for the COVID-19 treatment and the responses to the social demands of local communities. Methods: We worked with institutional documents from the national universities, the National Inter-University Council, the Ministry of Education and the Ministry of Science and Technology. We also used news sources, such as newspapers articles and the universities web sites. Results: Our research brought the attention to some interesting facts on the country's higher education system, which shows us a distinctive role that universities play in Argentina. Nevertheless, we have also found indicators regarding the difficulties that these institutions struggle with. In particular, these linked to the economic crises that the country has suffered for decades, which in turn have changed the universities specific features. Conclusion: The COVID-19 pandemic disrupted the functioning of society as a whole, and universities were no exception. Despite the strong heterogeneity that characterises national universities throughout the country, all of them agreed to make all their resources available to mitigate the effects of the health emergency.
Utilizing Student Time Series Behaviour in Learning Management Systems for Early Prediction of Course Performance
Author: Chen, Fu
Date: 2020-00-00
Type: Journal Articles
Subjects: Time on Task,Student Behavior,Integrated Learning Systems,Grade Prediction,Learning Analytics,Undergraduate Students,Foreign Countries

Predictive analytics in higher education has become increasingly popular in recent years with the growing availability of educational big data. Particularly, a wealth of student activity data is available from learning management systems (LMSs) in most academic institutions. However, previous investigations into predictive analytics in higher education using LMS activity data did not adequately accommodate student behaviours in the form of time series. In this study, we have applied a deep learning approach--long short-term memory (LSTM) networks--to analyze student online temporal behaviours using their LMS data for the early prediction of course performance. To reveal the potential of the deep learning approach in predictive analytics, we compared LSTM networks with eight conventional machine-learning classifiers in terms of the prediction performance as measured by the area under the ROC (receiver operating characteristic) curve (AUC) scores. Results indicate that using the deep learning approach, time series information about click frequencies successfully provided early detection of at-risk students with moderate prediction accuracy. In addition, the deep learning approach showed higher prediction performance and stronger generalizability than the machine learning classifiers.
The Development and Sustainability of School-Based Parent Networks in Low-Income Latinx Communities: A Mixed-Methods Investigation
Author: Rangel, David E.
Date: 2020-12-00
Type: Journal Articles
Subjects: Social Networks,Parent Participation,Elementary School Students,Parent Attitudes,Trust (Psychology),Hispanic Americans,Hispanic American Students,Family Programs,Interpersonal Relationship,Low Income Groups,Sustainability,Outcomes of Education,Program Descriptions,Parent School Relationship

Research suggests that school-based parent networks have significant benefits for children's education, yet scholars know very little about how such relationships form and develop over time. This study uses interview and survey data with elementary school parents in predominantly low-income Latinx communities to examine how parents meet one another; how deeper, more trusting relationships develop; and how the size and quality of parent networks change over time in the presence and absence of a family engagement program. Interview data suggest few and infrequent opportunities for parents to meet one another, which makes building relationships characterized by trust and shared expectations more difficult. The quantitative results show positive short-term effects of the program but differential effects over time.
Comparing Schedules of Progress Monitoring Using Curriculum-Based Measurement in Reading: A Replication Study
Author: Gesel, Samantha A.
Date: 2020-10-00
Type: Journal Articles
Subjects: Curriculum Based Assessment,Progress Monitoring,Students with Disabilities,Formative Evaluation,Special Education,Accuracy,Scheduling,Elementary School Students,Reading Achievement,Grade 2,Grade 3,Grade 4

Curriculum-based measurement (CBM) is a systematic, ongoing assessment framework that allows special educators to monitor students' progress and determine the need for instructional adaptations. Jenkins and colleagues examined the accuracy and timeliness of six different schedules of CBM progress monitoring (PM). The authors found that weekly and intermittent PM schedules were similarly accurate and timely. This study replicated and extended the work of Jenkins and colleagues by examining the accuracy and timeliness of different PM schedules for 51 students with disabilities. Results indicated that the accuracy and timeliness of the PM schedules for the current sample was poorer than the accuracy and timeliness reported by Jenkins and colleagues. In line with the results of the original study, however, these results indicated that intermittent PM schedules sufficiently predicted student true growth compared to weekly PM schedule. Implications for research and practice are discussed.
Research Ethics: Examining the Tension between Principlism and Rational Self-Interest in a Neoliberal University Context
Author: Le Grange, Lesley
Date: 2020-00-00
Type: Journal Articles
Subjects: Ethics,Research,Neoliberalism,Universities,Foreign Countries,Doctoral Students

Background: The reconfiguration of the contemporary university as a consequence of the (re)ascendency of neoliberal politics has not escaped South African universities. The higher education landscape in the country is characterised by performativity regimes -- discourses on quality assurance, efficiency and accountability abound and so too modes of regulation based on rewards, sanctions and censorship. Aim: The article explores the extent to which these two conflicting ethical discourses (principlism and rational self-interest) have a bearing on a South African case that resulted in an investigation into research misconduct at a South African university. Setting: The broader setting is the neoliberal university. The specific setting is Stellenbosch University. As is the case with many western(ised) universities, this higher education institution has not escaped neoliberal influences. Methods: The methods used combine conceptual exploration supported by a case study. The usage of case in this study does not refer to how it is typically used in qualitative research. The focus is not on a bounded system but on the narrative essence of the case, more akin to the usage of 'case' in law and medicine. Results: The philosophical tensions between the two discourses on ethics might be overcome by refocusing the university on the public good, instead of valorising the individual. Conclusion: Overcoming the philosophical tensions between the two discourses might only be possible through recognising the value of an immanent rather than a transcendent ethics.
How Can Predictive Learning Analytics and Motivational Interventions Increase Student Retention and Enhance Administrative Support in Distance Education?
Author: Herodotou, Christothea
Date: 2020-00-00
Type: Journal Articles
Subjects: Learning Analytics,Predictive Measurement,Student Motivation,Intervention,Program Effectiveness,Cost Effectiveness,School Holding Power,Academic Persistence,At Risk Students,Undergraduate Students,Open Universities,Learner Engagement,Distance Education,Identification,Telecommunications,Electronic Mail,Foreign Countries,Academic Support Services

Despite the potential of Predictive Learning Analytics (PLAs) to identify students at risk of failing their studies, research demonstrating effective application of PLAs to higher education is relatively limited. The aims of this study are: (1) to identify whether and how PLAs can inform the design of motivational interventions; and (2) to capture the impact of those interventions on student retention at the Open University UK. A predictive model -- the Student Probabilities Model (SPM) -- was used to predict the likelihood of a student remaining in a course at the next milestone and eventually completing it. Undergraduate students (N=630) with a low probability of completing their studies were randomly allocated into the control (n=312) and intervention groups (n=318), and contacted by the university Student Support Teams (SSTs) using a set of motivational interventions such as text, phone, and email. The results of the randomized control trial showed statistically significant better student retention outcomes for the intervention group, with the proposed intervention deemed effective in facilitating course completion. The intervention also improved the administration of student support at scale and low cost.
Real-Time Prediction of Students&apos; Activity Progress and Completion Rates
Author: Faucon, Louis
Date: 2020-00-00
Type: Journal Articles
Subjects: Classroom Techniques,Prediction,Learning Activities,Student Behavior,Time Factors (Learning),Predictor Variables,Undergraduate Students,Data Collection,Data Analysis,Models

In classrooms, some transitions between activities impose (quasi-)synchronicity, meaning there is a need for learners to move between activities at the same time. To make real-time decisions about when to move to the next activity, teachers need to be able to balance the progress of their students as they work at different paces. In this paper, we present a set of estimators that can be used in real time to predict the progress and completion rates of students working on computer-supported activities that can be divided into sequential subtasks. With our estimators, we investigate what effect the average progress rate of the class, a given number of previous steps, or weighting the proportion of progress assigned to each subtask has on predictions of students' progress. We find that accounting for the average class progress rate near the beginning of the activity can improve predictions over baseline. Additionally, weighted subtasks decrease prediction accuracy for activities where the behaviour of faster students diverges from the average behaviour of the class. This paper contributes to our ability to provide accurate student progress predictions and to understand the behaviour of students as they progress through the activity. These real-time predictions can enable teachers to optimize learning time in their classrooms.
Scaling the Student Journey from Course-Level Information to Program Level Progression and Graduation: A Model
Author: Munguia, Pablo
Date: 2020-00-00
Type: Journal Articles
Subjects: Learning Analytics,Courses,College Programs,Foreign Countries,Academic Achievement,College Students,Graduation,Program Design,Dropouts,Models

No course exists in isolation, so examining student progression through courses within a broader program context is an important step in integrating course-level and program-level analytics. Integration in this manner allows us to see the impact of course-level changes to the program, as well as identify points in the program structure where course interventions are most important. Here we highlight the significance of program-level learning analytics, where the relationships between courses become clear, and the impact of early-stage courses on program outcomes such as graduation or drop-out can be understood. We present a matrix model of student progression through a program as a tool to gain valuable insight into program continuity and design. We demonstrate its use in a real program and examine the impact upon progression and graduation rate if course-level changes were made early on. We also extend the model to more complex scenarios such as multiple program pathways and simultaneous courses. Importantly, this model also allows for integration with course-level models of student performance.