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Committee for Economic Development of The Conference Board, 2020
While the nation is enjoying its longest economic expansion on record and its lowest unemployment rate in 50 years, anxiety persists about how American businesses and workers will be affected by future changes in the labor market. Speculation about the "future of work" is typically centered on how new or emerging technologies could…
Descriptors: Job Skills, Employment Qualifications, Labor Market, Labor Needs
Perin, Dolores; Lauterbach, Mark – International Journal of Artificial Intelligence in Education, 2018
The problem of poor writing skills at the postsecondary level is a large and troubling one. This study investigated the writing skills of low-skilled adults attending college developmental education courses by determining whether variables from an automated scoring system were predictive of human scores on writing quality rubrics. The human-scored…
Descriptors: College Students, Writing Evaluation, Writing Skills, Developmental Studies Programs
Challco, Geiser C.; Andrade, Fernando R. H.; Borges, Simone S.; Bittencourt, Ig I.; Isotani, Seiji – Educational Technology & Society, 2016
Flow is the affective state in which a learner is so engaged and involved in an activity that nothing else seems to matter. In this sense, to help students in the skill development and knowledge acquisition (referred to as learners' growth process) under optimal conditions, the instructional designers should create learning scenarios that favor…
Descriptors: Instructional Design, Models, Learning Theories, Student Development
Ivaniushin, Dmitrii A.; Shtennikov, Dmitrii G.; Efimchick, Eugene A.; Lyamin, Andrey V. – International Association for Development of the Information Society, 2016
This paper describes an approach to use automated assessments in online courses. Open edX platform is used as the online courses platform. The new assessment type uses Scilab as learning and solution validation tool. This approach allows to use automated individual variant generation and automated solution checks without involving the course…
Descriptors: Online Courses, Evaluation Methods, Computer Assisted Testing, Large Group Instruction
Andres, Juan Miguel L.; Baker, Ryan S.; Gaševic, Dragan; Siemens, George; Spann, Catherine A. – Technology, Instruction, Cognition and Learning, 2017
There has been a considerable amount of research over the last few years devoted towards studying what factors lead to student success in online courses, whether for-credit or open. However, there has been relatively limited work towards formally studying which findings replicate across courses. In this paper, we present an architecture to…
Descriptors: Academic Achievement, Electronic Learning, Replication (Evaluation), Online Courses
Shum, Simon Buckingham; Sándor, Ágnes; Goldsmith, Rosalie; Bass, Randall; McWilliams, Mindy – Journal of Learning Analytics, 2017
When used effectively, reflective writing tasks can deepen learners' understanding of key concepts, help them critically appraise their developing professional identity, and build qualities for lifelong learning. As such, reflective writing is attracting substantial interest from universities concerned with experiential learning, reflective…
Descriptors: Reflection, Writing Assignments, Educational Research, Data Collection
Tansomboon, Charissa; Gerard, Libby F.; Vitale, Jonathan M.; Linn, Marcia C. – International Journal of Artificial Intelligence in Education, 2017
Supporting students to revise their written explanations in science can help students to integrate disparate ideas and develop a coherent, generative account of complex scientific topics. Using natural language processing to analyze student written work, we compare forms of automated guidance designed to motivate productive revision and help…
Descriptors: Automation, Guidance, Revision (Written Composition), Natural Language Processing
Higgins, Derrick; Heilman, Michael – Educational Measurement: Issues and Practice, 2014
As methods for automated scoring of constructed-response items become more widely adopted in state assessments, and are used in more consequential operational configurations, it is critical that their susceptibility to gaming behavior be investigated and managed. This article provides a review of research relevant to how construct-irrelevant…
Descriptors: Automation, Scoring, Responses, Test Wiseness
Liu, Ou Lydia; Brew, Chris; Blackmore, John; Gerard, Libby; Madhok, Jacquie; Linn, Marcia C. – Educational Measurement: Issues and Practice, 2014
Content-based automated scoring has been applied in a variety of science domains. However, many prior applications involved simplified scoring rubrics without considering rubrics representing multiple levels of understanding. This study tested a concept-based scoring tool for content-based scoring, c-rater™, for four science items with rubrics…
Descriptors: Science Tests, Test Items, Scoring, Automation
Reggiannini, Brian; Sheinkopf, Stephen J.; Silverman, Harvey F.; Li, Xiaoxue; Lester, Barry M. – Journal of Speech, Language, and Hearing Research, 2013
Purpose: In this article, the authors describe and validate the performance of a modern acoustic analyzer specifically designed for infant cry analysis.
Method: Utilizing known algorithms, the authors developed a method to extract acoustic parameters describing infant cries from standard digital audio files. They used a frame rate of 25 ms with a…
Descriptors: Acoustics, Automation, Statistical Analysis, Infants
Mousavi, Hamid; Kerr, Deirdre; Iseli, Markus R. – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2013
Ontologies are a vital component of most knowledge acquisition systems, and recently there has been a huge demand for generating ontologies automatically since manual or supervised techniques are not scalable. In this paper, we introduce "OntoMiner", a rule-based, iterative method to extract and populate ontologies from unstructured or…
Descriptors: Taxonomy, Automation, Artificial Intelligence, Graphs
Sottilare, Robert A. – Technology, Instruction, Cognition and Learning, 2018
This article is intended as a companion document to the more focused report provided by the author at the 2017 American Education Research Association (AERA) Conference as part of the Technology, Instruction, Cognition & Learning Special Interest Group's Symposium on Intelligent Tutoring Systems (ITSs). Both the AERA talk and this article…
Descriptors: Literature Reviews, Goal Orientation, Integrated Learning Systems, Instructional Design
Lottridge, Susan; Wood, Scott; Shaw, Dan – Applied Measurement in Education, 2018
This study sought to provide a framework for evaluating machine score-ability of items using a new score-ability rating scale, and to determine the extent to which ratings were predictive of observed automated scoring performance. The study listed and described a set of factors that are thought to influence machine score-ability; these factors…
Descriptors: Program Effectiveness, Computer Assisted Testing, Test Scoring Machines, Scoring
Paquette, Luc; Lebeau, Jean-François; Beaulieu, Gabriel; Mayers, André – International Journal of Artificial Intelligence in Education, 2015
Model-tracing tutors (MTTs) have proven effective for the tutoring of well-defined tasks, but the pedagogical interventions they produce are limited and usually require the inclusion of pedagogical content, such as text message templates, in the model of the task. The capability to generate pedagogical content would be beneficial to MTT…
Descriptors: Intelligent Tutoring Systems, Intervention, Instruction, Automation
Romero, Lucila; North, Matthew; Gutiérrez, Milagros; Caliusco, Laura – Educational Technology & Society, 2015
The use of ontologies as tools to guide the generation, organization and personalization of e-learning content, including e-assessment, has drawn attention of the researchers because ontologies can represent the knowledge of a given domain and researchers use the ontology to reason about it. Although the use of these semantic technologies tends to…
Descriptors: Electronic Learning, Taxonomy, Networks, Evaluation