The Experts below are selected from a list of 33 Experts worldwide ranked by ideXlab platform
Neil T Heffernan - One of the best experts on this subject based on the ideXlab platform.
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predicting student performance on post requisite Skills using Prerequisite Skill data an alternative method for refining Prerequisite Skill structures
Learning Analytics and Knowledge, 2016Co-Authors: Seth Adjei, Anthony F Botelho, Neil T HeffernanAbstract:Prerequisite Skill structures have been closely studied in past years leading to many data-intensive methods aimed at refining such structures. While many of these proposed methods have yielded success, defining and refining hierarchies of Skill relationships are often difficult tasks. The relationship between Skills in a graph could either be causal, therefore, a Prerequisite relationship (Skill A must be learned before Skill B). The relationship may be non-causal, in which case the ordering of Skills does not matter and may indicate that both Skills are Prerequisites of another Skill. In this study, we propose a simple, effective method of determining the strength of pre-to-post-requisite Skill relationships. We then compare our results with a teacher-level survey about the strength of the relationships of the observed Skills and find that the survey results largely confirm our findings in the data-driven approach.
Schmid Amanda - One of the best experts on this subject based on the ideXlab platform.
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Interventions for K-2 Students within the Special Education Classroom to Improve Self-Regulation before transitioning back into the General Education Classroom
theRepository at St. Cloud State, 2019Co-Authors: Schmid AmandaAbstract:This study looks at three kindergarten and first-grade students that all qualify under the category of Emotional or Behavioral Disorders. These students spend the majority of their day in the special education resource room. They are all on an Individualized Education Plan (IEP), and at a federal setting III. These students have all displayed a difficult time with following directions, staying on task, and coping age-appropriately. this paper discusses their individual needs more in the participants\u27 section in chapter two. The focus of this paper will be Chapter 4 in Conscious Discipline; Composure which is included in the second component, Safety. “Composure is self-regulation in action. It is the Prerequisite Skill adults need before disciplining children” (Bailey, 2015). The main focus in this chapter that will be implemented is creating a safe space for students and teaching breathing techniques to reduce and manage stress, which then leads to the coping Skills. The focus will be tracking the number of verbal prompts from an adult the students need to appropriately cope with the situation that has them escalated or in the blue, yellow or red zone. This study is a single subject with multiple baselines. The findings were positive, however with only 3 participants there was no test of inferential statistics to test if there was a statistically significant difference
Ackerman-hicks, Elizabeth L. - One of the best experts on this subject based on the ideXlab platform.
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An exploration of the effect of the development of spatial awareness as a Prerequisite science, technology, engineering, and math (STEM) Skill on the STEM gender achievement gap: an innovation study
University of Southern California. Libraries, 2018Co-Authors: Ackerman-hicks, Elizabeth L.Abstract:2018-04-09There is a gender gap in the college and career pipeline for science, technology, engineering and math (STEM) in the United States today. Through literature review, this study identified leaks along the educational pipeline and found that one particular Skill, the Prerequisite STEM Skill of spatial awareness, could hold a key to preparing young women for high-level STEM courses. Nationally, the gap in spatial awareness Skills between males and females is one of the mitigating factors in STEM course completion for females. Although spatial awareness can be learned within a fairly short period of time, this important Skill for STEM success is not often intentionally taught in schools. The purpose of this study was to explore the intentional teaching of spatial awareness by examining lesson design at The Academy, a unique all-girls school, that is geographically, racially, and economically diverse and is located in a large urban setting. Using Clark and Estes’s (2008) gap analysis as a general frame, this study explored the knowledge and motivation of the key stakeholder group, teachers at The Academy, to collaboratively plan and deliver spatial awareness lessons, which were initially implemented with sixth grade girls. The study reviewed the literature in several areas: leadership within an innovative educational environment, elements of teacher leadership, collaboration, and the development of a culture of innovation within a public educational setting. Using qualitative research methods including document analysis, survey, observation, and interviews, the study found that teachers collaboratively developed and implemented lessons that were research based, hands-on, and collaborative. After being exposed to these lessons, students showed a great deal of growth in spatial Skills within a short period of time. Although this was a small study conducted in a unique organization, it shows promise as an initial design for developing spatial awareness lessons to build this Prerequisite Skill for later STEM course success. Further longitudinal research is needed to analyze how teaching this Skill affects Skill development over time and girls’ future STEM course success
Adjei, Seth Akono - One of the best experts on this subject based on the ideXlab platform.
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Refining Prerequisite Skill Structure Graphs Using Randomized Controlled Trials
Digital WPI, 2018Co-Authors: Adjei, Seth AkonoAbstract:Prerequisite Skill structure graphs represent the relationships between knowledge components. Prerequisite structure graphs also propose the order in which students in a given curriculum need to be taught specific knowledge components in order to assist them build on previous knowledge and improve achievement in those subject domains. The importance of accurate Prerequisite Skill structure graphs can therefore not be overemphasized. In view of this, many approaches have been employed by domain experts to design and implement these Prerequisite structures. A number of data mining techniques have also been proposed to infer these knowledge structures from learner performance data. These methods have achieved varied degrees of success. Moreover, to the best of our knowledge, none of the methods have employed extensive randomized controlled trials to learn about Prerequisite Skill relationships among Skills. In this dissertation, we motivate the need for using randomized controlled trials to refine Prerequisite Skill structure graphs. Additionally, we present PLACEments, an adaptive testing system that uses a Prerequisite Skill structure graph to identify gaps in students’ knowledge. Students with identified gaps are assisted with more practice assignments to ensure that the gaps are closed. PLACEments additionally allows for randomized controlled experiments to be performed on the underlying Prerequisite Skill structure graph for the purpose of refining the structure. We present some of the different experiment categories which are possible in PLACEments and report the results of one of these experiment categories. The ultimate goal is to inform domain experts and curriculum designers as they create policies that govern the sequencing and pacing of contents in learning domains whose content lend themselves to sequencing. By extension students and teachers who apply these policies benefit from the findings of these experiments
Seth Adjei - One of the best experts on this subject based on the ideXlab platform.
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predicting student performance on post requisite Skills using Prerequisite Skill data an alternative method for refining Prerequisite Skill structures
Learning Analytics and Knowledge, 2016Co-Authors: Seth Adjei, Anthony F Botelho, Neil T HeffernanAbstract:Prerequisite Skill structures have been closely studied in past years leading to many data-intensive methods aimed at refining such structures. While many of these proposed methods have yielded success, defining and refining hierarchies of Skill relationships are often difficult tasks. The relationship between Skills in a graph could either be causal, therefore, a Prerequisite relationship (Skill A must be learned before Skill B). The relationship may be non-causal, in which case the ordering of Skills does not matter and may indicate that both Skills are Prerequisites of another Skill. In this study, we propose a simple, effective method of determining the strength of pre-to-post-requisite Skill relationships. We then compare our results with a teacher-level survey about the strength of the relationships of the observed Skills and find that the survey results largely confirm our findings in the data-driven approach.