ethanporcaro/eric-fulltext-meta huggingface dataset:
A Review of State-Level Procedural Guidance for Implementing Multi-Tiered Systems of Behavioral Support (MTSS-B)
Author: Briesch, Amy M.
Date: 2019-00-00
Type: Information Analyses
Subjects: State Departments of Education,Program Implementation,Positive Behavior Supports,Best Practices,Guidance,School Districts,Intervention,Progress Monitoring,Evidence Based Practice,Decision Making

Given the authority of state government over public education, one means of narrowing the best-practice to actual-practice gap in education is by putting forth clear state guidance and recommendations to schools. To date, however, little is known about the national landscape of procedural guidance that is readily available to practitioners looking to implement multi-tiered systems of support for behavior (MTSS-B). The purpose of the current study was to conduct a systematic review of state department of education websites in order to understand what guidance is afforded to local education agencies regarding MTSS-B. Results supported that roughly half of the states provided some form of procedural guidance for MTSS-B; however, both the type (e.g., what interventions to use, how often to progress monitor) and level of guidance varied widely. When states did provide behaviorally-specific guidance, documents were most likely to include specification of what types of interventions and measures to utilize; information less typically focused on assessment such as indications as to how often data should be collected and reviewed or what decision rule(s) should be used to determine student responsiveness. Implications for local implementation and strengthening future state-level guidance for MTSS-B are discussed. [This paper was published in &quot;Journal of Positive Behavior Interventions.&quot;]
Cumulative Evaluation of Empowering Families
Author: Roberts, Joanne
Date: 2019-09-09
Type: Reports - Research
Subjects: Elementary Schools,Intervention,Family Involvement,Teacher Role,School Role,Capacity Building,Social Development,Emotional Development,Cognitive Development,Executive Function,Empowerment,Self Efficacy,Reinforcement,Parent Teacher Cooperation,Interpersonal Communication,Program Effectiveness,Preschool Education,Elementary School Teachers,Parent Background,Educational Attainment,Language Usage,English,Spanish,Learning Strategies,Modeling (Psychology),Parenting Styles,Mothers

Empowering Families was focused on infusing the Providence Public School District (PPSD) elementary schools with an intervention centered on the Mind in the Making (MITM) training, designed to build the capacity of families, teachers, and schools to understand how children's executive function impacts social-emotional and cognitive growth. Data indicated that Empowering Families appeared to positively impact multiple factors included in this model of parental involvement. This includes factors such as parental motivations (e.g., efficacy and role construction); parental learning mechanisms (e.g., encouragement, modeling, instruction and reinforcement) and the importance placed on communication with parents by educators (e.g., invitation for involvement). In addition, Empowering Families also significantly predicted the importance parents placed on parent engagement activities. The report discusses findings in greater detail.
A Resource Guide for Reforming Developmental Education in the College Transition Space
Author: Kim, Jeanette
Date: 2020-00-00
Type: Guides - Non-Classroom
Subjects: Community Colleges,Educational Change,Developmental Studies Programs,Urban Universities,Remedial Programs,Program Effectiveness,Program Evaluation,Enrollment Rate,Remedial Reading,Writing (Composition),Remedial Mathematics,Information Management,Data Collection,Benchmarking

The City University of New York (CUNY) is the largest urban public university system in the United States with approximately 100,000 students enrolled in associate degree programs. Similar to trends nationwide, many associate degree students come to CUNY underprepared for college-level classes and are assigned to take remedial or developmental courses in reading, writing, or mathematics. Most of these students never complete their remedial coursework, much less earn a college degree. CUNY Start, a multifaceted prematriculation program, addresses these challenges to help underprepared students make a successful transition to college. Preliminary findings from a randomized control evaluation of CUNY Start found that CUNY Start students made more progress towards proficiency, had higher rates of re-enrollment, and attempted more college credits in the second semester than the control. As part of an IES funded research project, this resource guide has been developed for college administrators, faculty, and other key stakeholders interested in exploring the CUNY Start approach to remediation. The guide describes the CUNY Start program model, the use of research and evaluation practices, and the program's incorporation into large-scale changes to remedial policy at CUNY.
Academic Services in Islamic Education Management Study Program the Actualization of the Basic Values of the State Civil Apparatus at IAIN Palopo
Author: Ilham, Dodi
Date: 2020-09-00
Type: Journal Articles
Subjects: Islam,Religious Education,Efficiency,Information Systems,Action Research,Participatory Research,Academic Support Services,Management Development,Empathy,Web Sites,Computer Software,Ethics,Accountability,Institutional Mission,Foreign Countries,Nationalism,Administrators

This research aims to develop the MPI study program 's academic information to improve the efficiency and effectiveness of education services by web-based information systems by updating the State Civil Establishment (ASN) values, using the approach of Participatory Action Research (PAR). The solution to the issue of web-based academic services in IAIN Palopo's Islamic Education Management Study Programme, namely 1) conducting consultations related to web design of the Islamic Education Management Study Programme; 2) registering the web sub-domain and collecting materials that will be the content of the Islamic Education Management Study Program web.; 3) Installing web-based machines in registered sub-domains and creating a web-based framework for the Islamic Education Management Study Program; 4) designing a web-based display of the Islamic Education Management Study Program; 5) making menus and filling each menu with types of services, information, and activities related to the Islamic Education Management Study Program; 6) Implementation of web management training for prospective web administrators of Islamic Education Management Study Program; 7) Automation of web services published in the Islamic Education Management Study Program.
Serious Leisure Career in Students&apos; Career Future
Author: Ayyildiz Durhan, Tebessüm
Date: 2020-00-00
Type: Journal Articles
Subjects: College Students,Leisure Time,Career Development,Career Choice,Occupational Aspiration,Foreign Countries,Student Characteristics,Gender Differences,Student Attitudes,Knowledge Level,Intellectual Disciplines,Student Participation,Community

The aim of this research is to examine the current status of university students who are members of the university communities, through their activities in the communities, towards serious leisure and career future. At the same time, the extent to which some variables change these parameters and the impact of a serious leisure career on the future of the career were evaluated. In this context, &quot;Serious Leisure Career&quot; which is developed by Ayyildiz, Özdemir and Karaküçük (2020) and &quot;Career Futures Inventory (CFI)&quot; which is developed by Rottinghaus, Day and Borgen, (2005), translated to Turkish culture by Agargün et al., (2005) and which is evaluated about psychometric properties in Turkish sample by Kalafat (2012) is used. While analysis; descriptive statistics, independent sample T test, one-way analysis of variance (ANOVA) test, Tukey (HSD-LSD) test, Pearson Correlation test and regression analysis were used for in-group comparisons. As a result of the research, it can be said that serious leisure and career future are differentiated by certain variables and serious leisure career, which is an important factor affecting future career, is a tool to increase positive perception of career.
Empirical Research on the Relationship between Family Economic, Social and Cultural Status and Students&apos; Exposure to School Bullying: Mediating Effects of Parental Support and Teacher Support
Author: Huang, Liang
Date: 2019-00-00
Type: Journal Articles
Subjects: Family Characteristics,Family Income,Socioeconomic Background,Cultural Background,Bullying,Parent Role,Teacher Role,Social Support Groups,Socialization,Peer Relationship,Prevention,Disadvantaged Youth,Foreign Countries,International Assessment,Secondary School Students,Victims,Predictor Variables

Using survey data collected by the Organization for the Economic Cooperation and Development (OECD) in its 2015 Program for International Student Assessment (PISA2015), this study explores the relationship between family economic, social and cultural status (ESCS) and students' exposure to school bullying for students in Beijing-Shanghai-Jiangsu-Guangdong (China). Additionally, the study examines the mediating effects of parental support and teacher support on the relationship between family ESCS and students' exposure to school bullying. Lower family ESCS led to significantly increased exposure to school bullying. Parental support and teacher support mediated the relationship between family ESCS and students' exposure to school bullying, with slightly different magnitudes. The results suggest that China should continue to improve its system for school bullying prevention and treatment, and should especially focus on reducing bullying victimization among students from disadvantaged backgrounds. Further, parents in disadvantaged families should provide support and care to their children to enhance their abilities to tackle bullying victimization, and teachers should treat students fairly and guide students in socializing with their peers appropriately.
Academic Integrity: A Systems Approach to Address Contract Cheating
Author: Eaton, Sarah Elaine
Date: 2020-09-24
Type: Speeches/Meeting Papers
Subjects: Integrity,Cheating,Contracts,Systems Approach,Prevention,Plagiarism,Higher Education,Stakeholders,Foreign Countries

In this session, Eaton examines how a systems approach is needed to address contract cheating in its various forms. Using the 4M framework, Eaton demonstrates the role of the individual (micro), the department (meso), the learning organization (macro) and stakeholders beyond the institution (mega). In this session, Eaton shares insights from her forthcoming book, &quot;Plagiarism in Higher Education: Tackling Tough Topics in Academic Integrity&quot; to be published by ABC Clio/Libraries Unlimited in 2021.
Dynamic Knowledge Embedding and Tracing
Author: Xu, Liangbei
Date: 2020-07-00
Type: Speeches/Meeting Papers
Subjects: Artificial Intelligence,Learning Analytics,Computer Assisted Instruction,Student Evaluation

The goal of knowledge tracing is to track the state of a student's knowledge as it evolves over time. This plays a fundamental role in understanding the learning process and is a key task in the development of an intelligent tutoring system. In this paper we propose a novel approach to knowledge tracing that combines techniques from matrix factorization with recent progress in recurrent neural networks (RNNs) to effectively track the state of a student's knowledge. The proposed &quot;DynEmb&quot; framework enables the tracking of student knowledge even without the concept/skill tag information that other knowledge tracing models require while simultaneously achieving superior performance. We provide experimental evaluations demonstrating that DynEmb achieves improved performance compared to baselines and illustrating the robustness and effectiveness of the proposed framework. We also evaluate our approach using several real-world datasets showing that the proposed model outperforms the previous state-of-the-art. These results suggest that combining embedding models with sequential models such as RNNs is a promising new direction for knowledge tracing. [For the full proceedings, see ED607784.]
EDM and Privacy: Ethics and Legalities of Data Collection, Usage, and Storage
Author: Klose, Mark
Date: 2020-07-00
Type: Speeches/Meeting Papers
Subjects: Privacy,Learning Analytics,Data Collection,Information Storage,Social Networks,Ethics,Compliance (Legal),Student Records,Disclosure,Identification,Interaction,Access to Information,Risk,Policy Formation,Foreign Countries,Educational Legislation,Evaluation Utilization

Imagine a student using an intelligent tutoring system. A researcher records the correctness and time of each of your attempts at solving a math problem, nothing more. With no names, no birth dates, no connections to the school, you would think it impossible to track the answers back to the class. Yet, class sections have been identified with no more data than this. This paper recounts shocking episodes where educational data was used to re-identify individual students, build profiles on students, and commit fraud. We look at the ethical principles that underlie privacy as it relates to research data, and discuss ethical issues in data mining relating to social networks and big data. We explore four major types of data used in EDM [educational data mining]: (i) clickstream data, (ii) student-interaction data, (iii) evaluative data, and (iv) demographic data. Each type of data can be harmful if disclosed in particular contexts, even if all personally identifiable information is removed. We consider laws and legal precedents controlling access to student data in the United States and the European Union. This paper concludes by describing some practical situations in EDM and suggesting privacy policies that satisfy the ethical concerns raised earlier in the paper. [For the full proceedings, see ED607784.]
Dynamic Knowledge Tracing through Data Driven Recency Weights
Author: Agarwal, Deepak
Date: 2020-07-00
Type: Speeches/Meeting Papers
Subjects: Intelligent Tutoring Systems,Models,Skill Development,Mastery Learning,Bayesian Statistics,Markov Processes

There has been considerable interest in techniques for modelling student learning across practice problems to drive real-time adaptive learning, with particular focus on variants of the classic Bayesian Knowledge Tracing (BKT) model proposed by Corbett &amp; Anderson, 1995. Over time researches have proposed many variants of BKT with differentiation based on their treatment of the underlying parameters: (a) general across student and questions; (b) individualized for students; and (c) individualized for questions. Yet at the same time, most of these variants are similar in that they utilize the same Hidden Markov (HMM) architecture to model student learning and share many of the same drawbacks, including less effective balancing between recent and historical student data and assuming that students learn at the same rate across all the attempts irrespective of if they get the question right. At the same time, these variants share the virtue of parameter interpretability, a virtue not seen in recent efforts to recast knowledge tracing as a deep learning problem. This paper proposes a different architecture that replaces learning rate with recency weights which capture student improvement wholly through data rather than assuming constant learning across attempts and manages recent and historical data more appropriately while retaining the interpretability of BKT parameters. The proposed model was tested on multiple public datasets from ASSISTments and Mindspark and performed similarly to classic BKT model on unseen data. [For the full proceedings, see ED607784.]
Effective Forum Curation via Multi-Task Learning
Author: Brahman, Faeze
Date: 2020-07-00
Type: Speeches/Meeting Papers
Subjects: Automation,Online Courses,Discussion Groups,Identification,Artificial Intelligence,Correlation,Data Analysis

Despite several advantages of online education, lack of effective student-instructor interaction, especially when students need timely help, poses significant pedagogical challenges. Motivated by this, we address the problems of automatically identifying posts that express confusion or urgency from Massive Open Online Course (MOOC) forums. To this end, we first investigate the extent to which the tasks of confusion detection and urgency detection are correlated so as to explore the possibility of utilizing a multitasking set-up. We then propose two LSTM-based [Long Short Term Memory-based] multitask learning frameworks to leverage shared information and transfer knowledge across these related tasks. Our experiments demonstrate that the approaches improve over single-task models. Our best-performing model is especially useful in identifying posts that express both confusion and urgency, which can be of particular relevance for forum curation. [For the full proceedings, see ED607784.]
Enhancing Student Competency Models for Game-Based Learning with a Hybrid Stealth Assessment Framework
Author: Henderson, Nathan
Date: 2020-07-00
Type: Speeches/Meeting Papers
Subjects: Competency Based Education,Game Based Learning,Student Evaluation,Evaluation Methods,Learner Engagement,High School Students,Middle School Students,Genetics,Secondary School Science,Models

In recent years, game-based learning has shown significant promise for creating engaging and effective learning experiences. Developing models that can predict whether students will struggle with mastering certain concepts could guide adaptive support to assist students with mastering those concepts. Game-based learning environments offer significant potential for unobtrusively assessing student learning without interfering with gameplay through stealth assessment. Prior work on stealth assessment has focused on a single machine learning technique such as dynamic Bayesian networks or long short-term memory networks; however, a single modeling technique often does not guarantee the best predictive performance for all concepts of interest. In this paper, we present a hybrid data-driven approach to stealth assessment for predicting students' mastery of concepts through interactions with a game-based learning environment for introductory genetics. Stealth assessment models utilize students' observed gameplay behaviors using challenge- and session-based features to predict students' learning outcomes on identified concepts. We present single-task and multi-task models for predicting students' mastery of concepts and the results suggest that the hybrid stealth assessment framework outperforms individual models and holds significant potential for predicting student competencies. [For the full proceedings, see ED607784.]
Exploring Coach-Teacher Interactions within a Practice-Based Coaching Partnership
Author: Shannon, Darbianne K.
Date: 2020-00-00
Type: Reports - Research
Subjects: Coaching (Performance),Professional Development,Preschool Teachers,Preschool Children,Disabilities,Evidence Based Practice,Verbal Communication,Time Management,Feedback (Response),Goal Orientation,Questioning Techniques,Positive Reinforcement,Observation,Program Effectiveness,Partnerships in Education,Problem Solving

Professional development (PD), which includes coaching, has demonstrated the capacity to affect preschool teachers' use of evidence-based practices. The present study explored how coaches facilitated conversations within practice-based coaching (PBC) partnerships. A direct behavioral observation coding system was developed to investigate: (1) the proportion of time spent in different conversational foci, including who initiated the conversation; (2) coach verbal behaviors; and (3) whether the conversation foci, initiations, and coach verbal behavior changed across three occasions for seven coach-teacher dyads. Results from the present study indicate coaches spent the largest proportion of time engaging in conversations with teachers focused on reflection and feedback, followed by goal setting and action planning. The coaches used verbal behaviors (supportive and constructive feedback, clarifying questions) as required by the coaching protocol across all sampled occasions. Variation in conversation foci, initiations, and coach verbal behavior across three sampled occasions was evident. [This is the online version of an article published in &quot;Topics in Early Childhood Special Education.&quot;]
Course Recommender Systems with Statistical Confidence
Author: Warnes, Zachary
Date: 2020-07-00
Type: Speeches/Meeting Papers
Subjects: Course Selection (Students),Automation,Validity,Prediction,Mathematics,Undergraduate Students,Foreign Countries

Selecting courses in an open-curriculum education program is a difficult task for students and academic advisors. Course recommendation systems nowadays can be used to reduce the complexity of this task. To control the recommendation error, we argue that course recommendations need to be provided together with &quot;statistical&quot; confidence. The latter can be used for computing a statistically valid set of recommended courses that contains courses a student is likely to take with a probability of at least 1-[epsilon] for a user-specified significance level [epilsilon]. For that purpose, we introduce a generic algorithm for course recommendation based on the conformal prediction framework. The algorithm is used for implementing two conformal course recommender systems. Through experimentation, we show that these systems accurately suggest courses to students while maintaining statistically valid sets of courses recommended. [For the full proceedings, see ED607784.]
Differential Responses to Personalized Learning Recommendations Revealed by Event-Related Analysis
Author: Dieter, Kevin C.
Date: 2020-07-00
Type: Speeches/Meeting Papers
Subjects: Individualized Instruction,Student Behavior,Time Management,Reading Programs,Blended Learning,Elementary School Students,Change,Student Reaction,Electronic Learning

Educators are increasingly embracing personalization in online and blended learning programs as a means of focusing students' investment of time and energy into learning plans that are best tailored to their individual needs. When personalized learning tools are deployed into structured learning environments like schools, however, educators and students must consider program provided recommendations alongside potentially immutable factors like set daily schedules, mandated curricula, and student needs in other content areas. These on-the-ground factors make researching the impacts of personalized learning challenging because they are difficult to measure directly, especially for digital programs deployed at scale. Inspired by a widely influential methodology in brain imaging, we tackled this challenge by employing an &quot;event-related&quot; approach that emphasizes changes in student behavior that are time-locked to changes in program provided usage recommendations. Our analysis reveals that while student usage time can often be quite far from the amount recommended, students nevertheless respond to changes in program recommendations by adjusting usage in a corresponding manner. We further extend this general approach to demonstrate that students more often stayed on track toward their end of year goals following a week where they met or exceeded their program provided recommendation. Through these examples, we demonstrate the value of an event-related approach towards understanding how personalized paths can positively influence student learning. [For the full proceedings, see ED607784.]