ethanporcaro/eric-fulltext-meta huggingface dataset:
Toward a Framework for Learner Segmentation
Author: Azarnoush, Bahareh
Date: 2013-00-00
Type: Journal Articles
Subjects: Online Courses,Females,Doctoral Programs,Graduate Students,Resilience (Psychology),Data Collection,Data Analysis,Grouping (Instructional Purposes),Case Studies,Standards,Randomized Controlled Trials

Effectively grouping learners in an online environment is a highly useful task. However, datasets used in this task often have large numbers of attributes of disparate types and different scales, which traditional clustering approaches cannot handle effectively. Here, a unique dissimilarity measure based on the random forest, which handles the stated drawbacks of more traditional clustering approaches, is presented. Additionally, a rule-based method is proposed for interpreting the resulting learner segmentations. The approach was implemented on a real dataset of users of the &quot;Career&quot;WISE online educational environment, designed to provide resilience training for women STEM doctoral students, and was shown to find stable and meaningful groups of users.
Beacon- and Schema-Based Method for Recognizing Algorithms from Students&apos; Source Code
Author: Taherkhani, Ahmad
Date: 2013-00-00
Type: Journal Articles
Subjects: Programming,Mathematics,Computer Science Education,Methods,Identification,Classification,College Freshmen,Introductory Courses

In this paper, we present a method for recognizing algorithms from students programming submissions coded in Java. The method is based on the concept of &quot;programming schemas&quot; and &quot;beacons&quot;. Schemas are high-level programming knowledge with detailed knowledge abstracted out, and beacons are statements that imply specific structures in a program. The method automatically searches for schemas from the given program and compares the extracted schemas with those from the knowledge base to recognize the algorithm-specific code for further processing. In the next step, several characteristics and beacons specific to the given algorithm are computed from the code. These characteristics and beacons are then used as the learning data and given to the C4.5 algorithm, which builds a classification tree that can be used to classify previously unseen implementations of algorithms. The method and its performance is demonstrated in the case of basic sorting algorithms and their variations implemented both in various learning resources, that is, textbooks and websites, (N = 209 programs) and in genuine student submissions in a first year data structures and algorithms course (N = 159). The empirical study conducted for evaluating the performance of the classification by leave-one-out cross-validation technique shows that the estimated true positive rate is 97.0%. The results demonstrate the feasibility of the idea of recognizing algorithms based on algorithm-specific programming schemas and beacons. The method can be used as white-box analysis to verify that students have implemented the required algorithm and to give feedback to students on their problematic implementations. We discuss the applications of the method from both teachers and students point of view.
Operation ARIES!: Methods, Mystery, and Mixed Models: Discourse Features Predict Affect in a Serious Game
Author: Forsyth, Carol M.
Date: 2013-00-00
Type: Journal Articles
Subjects: Intelligent Tutoring Systems,Scientific Methodology,Science Instruction,Educational Games,Computer Games,Undergraduate Students,College Science,Student Surveys,Metacognition,Psychological Patterns,Data Analysis,Prediction,Critical Thinking,Learning,Pretests Posttests,Factor Analysis,Correlation,Student Motivation,Dialogs (Language)

Operation ARIES! is an Intelligent Tutoring System that is designed to teach scientific methodology in a game-like atmosphere. A fundamental goal of this serious game is to engage students during learning through natural language tutorial conversations. A tight integration of cognition, discourse, motivation, and affect is desired to meet this goal. Forty-six undergraduate students from two separate colleges in Southern California interacted with Operation ARIES! while intermittently answering survey questions that tap specific affective and metacognitive states related to the game-like and instructional qualities of Operation ARIES!. After performing a series of data mining explorations, we discovered two trends in the log files of cognitive-discourse events that predicted self-reported affective states. Students reporting positive affect tended to be more verbose during tutorial dialogues with the artificial agents. Conversely, students who reported negative emotions tended to produce lower quality conversational contributions with the agents. These findings support a valence-intensity theory of emotions and also the claim that cognitive-discourse features can predict emotional states over and above other game features embodied in ARIES.
A Contextualized, Differential Sequence Mining Method to Derive Students&apos; Learning Behavior Patterns
Author: Kinnebrew, John S.
Date: 2013-00-00
Type: Journal Articles
Subjects: Data Analysis,Middle School Students,Information Retrieval,Student Behavior,Learning Processes,Metacognition,Pacing,Individualized Instruction,Questionnaires,Protocol Analysis,Technology Uses in Education,Cognitive Development,Educational Technology,Artificial Intelligence,Grade 8,Feedback (Response)

Computer-based learning environments can produce a wealth of data on student learning interactions. This paper presents an exploratory data mining methodology for assessing and comparing students' learning behaviors from these interaction traces. The core algorithm employs a novel combination of sequence mining techniques to identify deferentially frequent patterns between groups of students (e.g., experimental versus control conditions or high versus low performers). We extend this technique by contextualizing the sequence mining with information about the student's performance over the course of the learning interactions. Specifically, we employ a piecewise linear segmentation algorithm in concert with the differential sequence mining technique to identify and compare segments of students' productive and unproductive learning behaviors. We present the results from the application of this exploratory data mining methodology to learning interaction trace data gathered during a recent middle school class study with the Betty's Brain learning environment. These results illustrate the potential of this methodology in identifying learning behavior patterns relevant to the investigation of metacognition and strategy use.
Clustering and Profiling Students According to Their Interactions with an Intelligent Tutoring System Fostering Self-Regulated Learning
Author: Bouchet, Francois
Date: 2013-00-00
Type: Journal Articles
Subjects: Intelligent Tutoring Systems,Educational Technology,Technology Uses in Education,Individualized Instruction,Pacing,Statistical Analysis,Metacognition,Human Body,Physiology,Questionnaires,Pretests Posttests,Multiple Choice Tests,Randomized Controlled Trials,Eye Movements,Nonverbal Communication,Student Characteristics,Coding,Multivariate Analysis,Undergraduate Students

In this paper, we present the results obtained using a clustering algorithm (Expectation-Maximization) on data collected from 106 college students learning about the circulatory system with MetaTutor, an agent-based Intelligent Tutoring System (ITS) designed to foster self-regulated learning (SRL). The three extracted clusters were validated and analyzed using multivariate statistics (MANOVAs) in order to characterize three distinct profiles of students, displaying statistically significant differences over all 12 variables used for the clusters formation (including performance, use of note-taking and number of sub-goals attempted). We show through additional analyses that variations also exist between the clusters regarding prompts they received by the system to perform SRL processes. We conclude with a discussion of implications for designing a more adaptive ITS based on an identification of learners' profiles.
A First Step in Learning Analytics: Pre-Processing Low-Level Alice Logging Data of Middle School Students
Author: Werner, Linda
Date: 2013-00-00
Type: Journal Articles
Subjects: Electronic Learning,Learning Processes,Educational Research,Data Collection,Data Analysis,Middle School Students,Computer Software,Programming,Data,Problem Solving

Educational data mining can miss or misidentify key findings about student learning without a transparent process of analyzing the data. This paper describes the first steps in the process of using low-level logging data to understand how middle school students used Alice, an initial programming environment. We describe the steps that were required and the decisions that were made in building a tool to translate the low-level logging data into a form that can be used to investigate educational questions about problem-solving strategies for a range of different programming tasks. This work contributes to efforts to analyze educational data, and is important for researchers and tool builders involved with the design of logging systems for other programming environments and software tools.
Utilization of a High Stakes High School Graduation Exam to Assess the Impact of Agricultural Education: A Measure of Curriculum Integration
Author: Nolin, Joshua Brock
Date: 2013-00-00
Type: Journal Articles
Subjects: High Stakes Tests,Exit Examinations,Agricultural Education,High School Students,Program Effectiveness,Academic Achievement,Correlation,Standardized Tests,High Schools,Regression (Statistics),Models,Predictor Variables

Phipps, Osborne, Dyer, and Ball, (2008) posited that, &quot;Agricultural education in secondary schools has played an important role in enhancing student achievement in the core subject areas…&quot; (p. 4), while Enderlin and Osborne (1992) reported that agricultural students received higher test scores in biology than students in other science classes. However, further evaluation of this academic integration is warranted to determine which practices are most beneficial to students. This study sought to determine if there was a relationship between the number of agricultural education classes that students took and the subsequent outcomes on the Alabama High School Graduation Exam. To address the research question, binary logistic regression was employed. Results indicated that the model did predict the outcomes on the language and math portion of the exam while the model failed to predict outcomes on the social studies, biology, and reading portions of the exam. This study should be replicated using standardized tests in other states. Comparable data should be collected for students not enrolled in agriculture classes so that the groups mean scores could be compared.
Impacts of a Faculty Abroad Experience on Teaching Style and Technology Use in a College of Agriculture and Life Sciences
Author: Sandlin, M'Randa R.
Date: 2013-00-00
Type: Journal Articles
Subjects: Overseas Employment,College Faculty,Agricultural Education,Foreign Countries,Interviews,Teaching Styles,Technology Uses in Education,Educational Technology,Reflection,Program Effectiveness,Global Approach,Technology Integration,Qualitative Research

Faculty abroad programs are becoming a popular method to provide faculty in colleges of agriculture with international experiences so they may internationalize their curricula. These programs also serve to provide experiential faculty development opportunities. Eight faculty members from Texas A&amp;M University participated in a faculty abroad experience in Trinidad and Tobago and developed instructional materials using technology. Pre-reflective and reflective interview responses were qualitatively analyzed to determine the impact of this experience on participants' teaching style and technology usage. The comparison of the pre-reflective and reflective data sets indicated participants perceived impact on teaching style, specifically in relation to their curriculum content and use of global connections as it pertained to their discipline and global relationships with native counterparts. Many participants were already using technology in the classroom prior to the international experience. As a result of the experience, the level of their technology usage increased as they incorporated media, such as audio and video, to communicate their experiences and create context for their lessons. It was concluded that teaching style, technology usage, and excitement for teaching were renewed as a result of an international experience. Future studies should be conducted to compare these findings with similar faculty abroad experiences.
Developing Metrics for Effective Teaching in Extension Education: A Multi-State Factor-Analytic and Psychometric Analysis of Effective Teaching
Author: McKim, Billy R.
Date: 2013-00-00
Type: Journal Articles
Subjects: Psychometrics,Extension Education,Teacher Effectiveness,Teacher Competencies,Agricultural Education,Food,Natural Resources,Teaching Methods,Teacher Surveys,Observation,Self Evaluation (Individuals),Teacher Evaluation,Outcome Measures,Multivariate Analysis,Teacher Characteristics,Teacher Attitudes,Online Surveys,Statistical Analysis

To successfully educate the public about agriculture, food, and natural resources, we must have effective educators in both formal and nonformal settings. Specifically, this study, which is a valuable part of a larger sequential mixed-method study addressing effective teaching in formal and nonformal agricultural education, provides direction for future effective teaching research in extension education. Particularly, this study assessed 142 behaviors, characteristics, and techniques considered indicative of effective teaching, to reduce the number of competencies and identify constructs of effective teaching in extension education. A total of 1,470 extension educators from 30 states, surveyed in the fall of 2011, served as the population for this study. As a result, 63 effective teaching competencies in 11 constructs were identified. Psychometric evaluation of the 11 constructs resulted in Cronbach's alpha coefficients ranging from 0.82 to 0.93, supporting the reliability of the identified constructs. An expert panel then named the constructs, many of which aligned with those identified in previous teaching effectiveness research. Implications for practice and research resulted from this study, including a proposed three-part framework for assessing effective teaching in extension education, which includes self-evaluation, observation-based assessment, teaching-related output and/or outcome measures.
Should I Stay or Should I Go? Revisiting Influencing Factors of SPED Teacher Attrition &amp; Retention: A Review of the Literature
Author: Theoharis, Raschelle
Date: 2013-00-00
Type: Journal Articles
Subjects: Special Education Teachers,Teacher Persistence,Literature Reviews,Teacher Characteristics,Age Differences,Gender Differences,Racial Differences,Teacher Qualifications,Academic Degrees,Teacher Attitudes,Teaching Conditions,Teacher Salaries,School Culture,Teacher Role,Family Influence,Social Influences

Evidence continually reports that special education (SPED) teachers stay in the field three-to-five academic school years before leaving the profession. A systematic review of historical-to-current literature revealed that personal, employment, and external factors were the three most prevalent variables that influenced attrition and retention (A&amp;R) rates of SPED teachers. Although A&amp;R has significant implications for student learning outcomes, the focus of this article is on analyzing these casual factors in an attempt to revisit and revitalize this important issue.
A Comparison of Two Curricular Models of Professional Development to Increase Teacher Repertoires for Instructing Students with Autism
Author: Dille, Lisa
Date: 2013-00-00
Type: Journal Articles
Subjects: Autism,Faculty Development,Teacher Competencies,Knowledge Base for Teaching,Self Efficacy,Teaching Methods,Student Needs,Behavior Modification,Social Development,Emotional Development,Pretests Posttests,Experimental Groups,Control Groups,Comparative Analysis,Questionnaires,Statistical Analysis

This study compared the effectiveness of two curricular models of professional development to increase teacher repertoires for instructing students with autism. Specific focus was on the use of a Blended Model of professional development in comparison to a Behavioral Model of professional development in regard to increasing teacher knowledge, teacher self efficacy, teacher self report and teacher application of instructional methods, strategies, and learning supports with students with autism. The findings suggest that when the goal is to specifically increase teaching repertoires for applying instructional methods, strategies, and learning supports to students with both mild/moderate and severe autism the blending of both behavioral and socio-emotional approaches for teaching students with autism may be more effective.
Responses to Positive versus Negative Interventions to Disruptive Classroom Behavior in a Student with Attention Deficit Hyperactivity Disorder (ADHD)
Author: Brown, Renee B.
Date: 2013-00-00
Type: Journal Articles
Subjects: Intervention,Behavior Problems,Behavior Modification,Student Behavior,Attention Deficit Hyperactivity Disorder,Males,Preadolescents,Program Effectiveness,Positive Reinforcement,Response to Intervention,Hypothesis Testing

This study reviews pertinent research, then uses a single-subject experimental design and methodology to assess the impact of both positive and negative interventions to reduce the incidence of inappropriate classroom behavior in a 12.2 year-old male student with Attention Deficit Hyperactivity Disorder (ADHD). In the context of this study, inappropriate classroom behavior is defined as speaking out inappropriately in class. Evaluation of the data indicates several methods that (a) succeed in reducing instances of inappropriate behavior, and (b) demonstrated synergistic effects when used in combination. While not eliminated completely, instances of this inappropriate behavior were reduced from 5.2 instances per class session to less than one instance per class session.
General Education Teachers&apos; Knowledge of and Attitudes toward Students with Attention Deficit/Hyperactivity Disorders: Are They Still Being Overlooked and Underserved?
Author: Wallace Taylor, Roben
Date: 2013-00-00
Type: Journal Articles
Subjects: Teacher Attitudes,Knowledge Level,Attention Deficit Hyperactivity Disorder,Student Characteristics,Symptoms (Individual Disorders),Teaching Skills,Teacher Competencies,Inclusion,Pretests Posttests,Workshops,Faculty Development,Questionnaires,Delphi Technique,Interviews,Elementary Secondary Education,Qualitative Research,Likert Scales,Statistical Analysis

This study was an investigation of general education teachers' knowledge and attitudes regarding students with Attention Deficit/Hyperactivity Disorder (AD/HD). Of interest were (a) the extent of teachers' knowledge about characteristics of AD/HD; (b) the extent of teachers' knowledge of teacher skills appropriate for educating students with AD/HD; and (c) the extent of teachers' willingness to accommodate students with AD/HD. There was an initial assessment of teachers' knowledge and attitudes (pretest) followed by a workshop designed to increase teachers' knowledge and improve their attitudes. An additional assessment of their knowledge and attitudes (posttest) was then administered. Results and implications for future research are discussed within this article.
Working Together for Learning Together: Supporting Students and Teachers with Collaborative Instruction
Author: Shamberger, Cynthia Thrasher
Date: 2013-00-00
Type: Journal Articles
Subjects: Teacher Collaboration,Team Teaching,Teaching Methods,Literature Reviews,Inclusion,Student Diversity,Educational Legislation,Disabilities,Equal Education,Federal Legislation,Court Litigation,Access to Education,Faculty Development,Barriers,Teacher Education Programs,Time,Scheduling,Teaching Conditions,Attitudes

Professional educators are called upon to provide effective instruction to student populations that increasingly consist of multiple cultures, languages, and ethnic backgrounds. Based on current special education law, schools are working toward establishing more collaborative cultures by stressing partnerships between general and special education teachers, which often includes initiating inclusive practices such as co-teaching. This article reviews the professional literature regarding the inception of inclusive practices and the factors that influenced this concept in the field. Particularly, skills for collaboration and the practice of co-teaching are examined in the context of the developing trend toward more collaborative interactions in school setting.
Special Educator Evaluation: Cautions, Concerns and Considerations
Author: Semmelroth, Carrie L.
Date: 2013-00-00
Type: Journal Articles
Subjects: Special Education Teachers,Teacher Evaluation,Models,Alternative Assessment,Teacher Effectiveness,Evidence Based Practice,Outcomes of Education,Effect Size,Alignment (Education),Student Educational Objectives,Value Added Models,Classroom Observation Techniques,Evaluation Methods

There is currently little consensus on how special education teachers should be evaluated in a way that is effective, fair and responsive to their unique teaching responsibilities. In this paper, we explain several of the current approaches to teacher evaluation under consideration, and then provide an overview of the challenges associated with the use of these models for special education teachers. We describe a model currently under development that is designed to better meet the unique characteristics of special education teacher evaluation. Our alternative approach proposes to evaluate special education teacher effectiveness through two primary components: observations of the special educator's use of research-based instructional practices, and the resulting student outcomes reported through effect sizes on measures aligned with relevant student goals.
Preparing Preservice Teachers to Address Bullying through Cartoon Lessons
Author: Rule, Audrey C.
Date: 2013-00-00
Type: Journal Articles
Subjects: Preservice Teachers,Bullying,Teaching Methods,Cartoons,Special Education,At Risk Students,Disabilities,Practicums,Elementary School Students,Student Behavior,Special Education Teachers,Student Attitudes,Program Effectiveness,Classroom Environment,Questionnaires,Qualitative Research

Students who qualify for special education services are at risk for being bullied because of their cognitive, emotional, behavioral, or physical differences. Currently, teachers are not effective enough in reducing bullying; better preservice teacher preparation in this area may help to alleviate the problem. The current study explored the effects of preservice teachers using cartoons to spark discussion of bullying issues during practicum experiences with elementary students at urban schools. Twenty-one preservice special education teachers participated in the mostly qualitative study that presented an analysis of their reflections after teaching three cartoon-focused lessons on bullying to students in small groups, each containing at least one student with special needs. Reflections revealed the success of the cartoon lessons with positive effect on classroom climate. Preservice special education teachers became aware of the motivating effects of cartoons, the pervasiveness of bullying and the eagerness of elementary students to discuss it.