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Sonst. PersonenLynch, Collin F. (Hrsg.); Merceron, Agathe (Hrsg.); Desmarais, Michel (Hrsg.); Nkambou, Roger (Hrsg.)
InstitutionInternational Educational Data Mining Society
TitelProceedings of the International Conference on Educational Data Mining (EDM) (12th, Montreal, Canada, July 2-5, 2019)
Quelle(2019), (823 Seiten)
PDF als Volltext kostenfreie Datei Verfügbarkeit 
Spracheenglisch
Dokumenttypgedruckt; online; Monographie
ISBN978-1-7336736-0-0
SchlagwörterTagungsbericht; Data Collection; Data Analysis; Information Retrieval; Content Analysis; Educational Research; Ethics; Evidence Based Practice; Grade Point Average; Inquiry; Game Based Learning; Metacognition; Student Records; Undergraduate Students; Predictor Variables; Student Satisfaction; Skill Development; Prediction; Programming; Large Group Instruction; Online Courses; Dropouts; Academic Achievement; Computation; Models; Time to Degree; Measurement Techniques; Institutional Characteristics; Help Seeking; Student Motivation; Artificial Intelligence; Interaction; Teaching Methods; Knowledge Level; Video Games; Cooperative Learning; Problem Solving; Grades (Scholastic); Reinforcement; Intelligent Tutoring Systems; Learning Activities; Graphs; Semantics; Difficulty Level; Affective Behavior; Telecommunications; Handheld Devices; Feedback (Response); English (Second Language); Second Language Instruction; Language Teachers; Concept Formation; Prior Learning; Grouping (Instructional Purposes); Tests; Scores; Markov Processes; Enrollment Trends; Man Machine Systems; Classification; Eye Movements; Physiology; Motion; Equipment; Academic Failure; Science Instruction; Educational Games; Misconceptions; Error Patterns; Active Learning; Writing Processes; Mathematics Skills; Success; Test Selection; Creativity; Geometry; Second Language Learning; Interpersonal Communication; Academic Language; Peer Evaluation; Emotional Response; Student Characteristics; Gender Differences; Electronic Mail; Student Attitudes; Cheating; Educational Administration; Justice; Natural Language Processing; College Students; Student Behavior; Automation; Scoring; Essays; Mandarin Chinese; Tone Languages; Parent Role; Mathematics Instruction; Experiential Learning; Individual Differences; Search Strategies; Visualization; Performance Based Assessment; Independent Study; Grade 8; Mathematics Achievement; Writing Skills; High School Students; Web Based Instruction; Instructional Materials; Graduates; Employment; Minority Group Students; At Risk Students; Program Effectiveness; Resource Units; Educational Needs; STEM Education; Career Choice; Video Technology; Social Values; Moral Values; Thinking Skills; Student Evaluation; Integrated Learning Systems; Error Correction; Foreign Countries; Grading; Social Influences; Friendship; Item Response Theory; Grammar; Cooperation; Elective Courses; Course Selection (Students); Modeling (Psychology); Reaction Time; Homework; Liberal Arts; Young Children; Computer Software; Brazil

Data capture; Datensammlung; Auswertung; Inhaltsanalyse; Bildungsforschung; Pädagogische Forschung; Ethik; Meta cognitive ability; Meta-cognition; Metakognitive Fähigkeit; Metakognition; Schülerakte; Prädiktor; Kompetenzentwicklung; Qualifikationsentwicklung; Vorhersage; Programmierung; Online course; Online-Kurs; Drop-out; Drop-outs; Dropout; Early leavers; Schulversagen; Schulleistung; Analogiemodell; Messtechnik; Help-seeking behavior; Help-seeking behaviour; Hilfe suchendes Verhalten; Schulische Motivation; Künstliche Intelligenz; Interaktion; Teaching method; Lehrmethode; Unterrichtsmethode; Wissensbasis; Video game; Videospiel; Videospiele; Kooperatives Lernen; Problemlösen; Notenspiegel; Positive Verstärkung; Intelligentes Tutorsystem; Lernaktivität; Grafische Darstellung; Semantik; Schwierigkeitsgrad; Affective disturbance; Active behaviour; Affektive Störung; Telekommunikationstechnik; English as second language; English; Second Language; Englisch als Zweitsprache; Fremdsprachenunterricht; Language teacher; Sprachunterricht; Concept learning; Begriffsbildung; Vorkenntnisse; Grouping; Gruppenbildung; Examination; Prüfung; Examen; Markowscher Prozess; Mensch-Maschine-System; Classification system; Klassifikation; Klassifikationssystem; Augenbewegung; Physiologie; Bewegungsablauf; Teaching of science; Science education; Natural sciences Lessons; Naturwissenschaftlicher Unterricht; Educational game; Lernspiel; Missverständnis; Fehlertyp; Aktives Lernen; Mathmatics achievement; Mathematics ability; Mathematische Kompetenz; Erfolg; Testauswahl; Kreativität; Geometrie; Zweitsprachenerwerb; Interpersonale Kommunikation; Academic; Language; Languages; Akademiker; Sprache; Wissenschaftssprache; Emotionales Verhalten; Geschlechterkonflikt; Elektronischer Briefkasten; Schülerverhalten; Prellen; Bildungsverwaltung; Schuladministration; Schulverwaltung; Gerechtigkeit; Natürliche Sprache; Collegestudent; Student behaviour; Bewertung; Essay; Aufsatzunterricht; Tonsprache; Parental role; Elternrolle; Mathematics lessons; Mathematikunterricht; Experiental learning; Erfahrungsorientiertes Lernen; Individueller Unterschied; Suchstrategie; Visualisation; Visualisierung; Leistungsermittlung; Selbststudium; School year 08; 8. Schuljahr; Schuljahr 08; Mathmatics sikills; Mathematical ability; Writing skill; Schreibfertigkeit; High school; High schools; Student; Students; Oberschule; Schüler; Schülerin; Studentin; Web Based Training; Lehrmaterial; Lehrmittel; Unterrichtsmedien; Graduate; Absolvent; Absolventin; Hochschulabsolvent; Hochschulabsolventin; Dienstverhältnis; Educational need; Bildungsbedarf; STEM; Sozialer Wert; Moral value; Ethischer Wert; Denkfähigkeit; Schulnote; Studentische Bewertung; Korrektur; Ausland; Notengebung; Sozialer Einfluss; Freundschaft; Item-Response-Theorie; Grammatik; Co-operation; Kooperation; Elective course; Wahlkurs; Course selection; Kurswahl; Modeling; Modelling; Modellierung; Reaktionsvermögen; Hausaufgabe; Frühe Kindheit; Brasilien
AbstractThe 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks such as writing, design, and collaborative problem solving, and it has been used in new informal contexts where student actions are at best semi-structured. This iteration of the conference includes a range of work in these and other areas. This year's conference features three invited talks: Julita Vassileva, Professor at the Department of Computer Science, University of Saskatchewan, Canada; Steve Ritter, Co-Founder and Chief Scientist, Carnegie Learning Inc., Pittsburgh; and Michael Mozer, Professor Department of Computer Science and Institute of Cognitive Science University of Colorado. The number of accepted papers include 22 full papers and 42 short papers. An additional 47 papers were accepted to the poster track. The poster and demo track itself accepted 14 contributions out of 34 submissions. Together with the "Journal of Educational Data Mining" ("JEDM"), the EDM 2019 conference held a "JEDM" Track that provides researchers a venue to deliver more substantial mature work than is possible in a conference proceeding and to present their work to a live audience. The papers submitted to this track followed the "JEDM" peer review process. Two such papers are featured in the conference's program. Additionally this year, papers that were regularly published in the journal in 2018 were invited for presentation at the conference. Two authors accepted this invitation. The main conference invited contributions to an Industry Track in addition to the main track. The EDM 2019 Industry Track received eleven submissions of which six were accepted. The EDM conference continues its tradition of providing opportunities for young researchers to present their work and receive feedback from their peers and senior researchers. The doctoral consortium this year features eight such presentations. This year's conference includes also an invited talk by the authors of the 2018 winner of the EDM Test of Time Award. This year's talk is delivered by Mykola Pechenizkiy. In addition to the main program, there are three workshops: (1) Learning Analytics: Building bridges between the Education and the Computing communities; (2) Reinforcement Learning for Educational Data Mining; and (3) Workshop on EDM & Games: Leveling Up Engaged Learning with Data-Rich Analytics. Three tutorials were presented as well: (1) Sharing and Reusing Data and Analytic Methods with LearnSphere; (2) Causal Discovery with Tetrad in LearnSphere's Tigris and Designing and Developing Open; and (3) Pedagogically-Based Predictive Models using the Moodle Analytics API. (ERIC).
AnmerkungenInternational Educational Data Mining Society. e-mail: admin@educationaldatamining.org; Web site: http://www.educationaldatamining.org
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2020/1/01
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