Jovita Vytasek
Simon Fraser University
RecallMaturity (psychological)Study skillsComputer-mediated communicationMetacognitionWorld Wide WebCollaborative learningThread (computing)Developmental psychologyTracingIndependent studyMathematics educationSoftware systemArtificial intelligencePsychologyOperational definitionContent analysisEducational technologySet (psychology)Time managementDomain (software engineering)Test setTopic modelSoftware analyticsWork (electrical)Cognitive psychologySynchronous learningProcrastinationStudent engagementNatural language processingData scienceGeneralizability theoryBusiness intelligenceSelf-regulated learningCLARITYParagraphFocus (linguistics)Learning analyticsTransfer of trainingContent (measure theory)Design knowledgeLearning ManagementTask (project management)Digital learningAcademic achievementLinguistic modelPrior learningUndergraduate studentExperiential learningBusiness analyticsComputer scienceLinguisticsProcess (engineering)Reliability (statistics)Distance educationCooperative learningRhetorical modesEvent (computing)Meaning (linguistics)Cultural analyticsDocumentationTRACE (psycholinguistics)Big dataSocial psychologyAnalyticsPrecision and recallTeam learningCategorizationLearning sciencesCoherence (linguistics)
14Publications
8H-index
192Citations
Publications 14
Newest
#1Jovita Vytasek (SFU: Simon Fraser University)H-Index: 8
#2Alexandra Patzak (SFU: Simon Fraser University)H-Index: 4
Last. Philip H. Winne (SFU: Simon Fraser University)H-Index: 68
view all 3 authors...
Volumes of detailed information are now unobtrusively collected as students use learning management systems and digital learning environments in their studies. This significantly elevates opportunities to better understand how students learn. The learning analytics community is exploring these data to describe learning processes [117] and ground recommendations for improved learning environments [8, 102, 139]. One challenge in this work is need for more and more detailed information about each s...
12 CitationsSource
#1Philip H. Winne (SFU: Simon Fraser University)H-Index: 68
#2Kenny Teng (SFU: Simon Fraser University)H-Index: 1
Last. Jovita Vytasek (SFU: Simon Fraser University)H-Index: 8
view all 10 authors...
Data used in learning analytics rarely provide strong and clear signals about how learners process content. As a result, learning as a process is not clearly described for learners or for learning scientists. Gasevic, Dawson, and Siemens (2015) urged data be sought that more straightforwardly describe processes in terms of events within learning episodes. They recommended building on Winne’s (1982) characterization of traces — ambient data gathered as learners study that more clearly represent w...
9 CitationsSource
#1Jovita VytasekH-Index: 8
Mar 4, 2019 in LAK (Learning Analytics and Knowledge)
#1Jovita Vytasek (SFU: Simon Fraser University)H-Index: 8
#2Alexandra Patzak (SFU: Simon Fraser University)H-Index: 4
Last. Philip H. Winne (SFU: Simon Fraser University)H-Index: 68
view all 3 authors...
Revision is important but challenging for novice writers, particularly in post-secondary education where opportunities for personalized feedback are limited. Inexperienced writers typically overlook revision; when they do revise, they focus on surface errors rather than global revisions that enhance meaning and coherence. Writing analytics can automate personalized prompts to guide revision. We use topic modelling LDA as grounds for an analytic to scaffold holistic revision at paragraph and essa...
1 CitationsSource
#1Alexandra Patzak (SFU: Simon Fraser University)H-Index: 4
#2Jovita Vytasek (SFU: Simon Fraser University)H-Index: 8
Our systematic review analyzes operational definitions of TM, and identifies relations of TM to performance in post-secondary education and work contexts. A broad set of search terms were used to identify 227 sources; culled to 49 after review. Theoretical and operational definitions of TM vary considerably, limiting generalizability of empirical findings, clarity of recommendations, and opportunity to meta-analytically explore effect sizes. Procrastination consistently negatively related to TM....
#1Philip H. WinneH-Index: 68
#2John C. NesbitH-Index: 24
Last. Jason StewartH-Index: 1
view all 11 authors...
2 Citations
#1Jovita Vytasek (SFU: Simon Fraser University)H-Index: 8
#2Alyssa Friend Wise (NYU: New York University)H-Index: 26
Last. Sonya Woloshen (SFU: Simon Fraser University)H-Index: 2
view all 3 authors...
This paper explores the potential of using naive topic modeling to support instructors in navigating MOOC discussion forums. Categorizing discussion threads into topics can provide an overview of the discussion, improve navigation of the forum, and support replying to a representative sample of content related posts. We investigate four different approaches to using topic models to organize and present discussion posts, highlighting the strength and weaknesses of each approach to support instruc...
7 CitationsSource
#1Alyssa Friend Wise (NYU: New York University)H-Index: 26
#2Yi Cui (SFU: Simon Fraser University)H-Index: 7
Last. Jovita Vytasek (SFU: Simon Fraser University)H-Index: 8
view all 4 authors...
Abstract This study addresses overload and chaos in MOOC discussion forums by developing a model to categorize threads based on whether or not they are substantially related to course content. A linguistic model was built based on manually coded starting posts in threads from a statistics MOOC, and tested on the second offering of the course, another statistics MOOC, a psychology MOOC, a physiology MOOC, and a test set of reply posts. Results showed that content-related starting posts had distin...
51 CitationsSource
#1Philip H. WinneH-Index: 68
#2Jovita VytasekH-Index: 8
Last. John C. NesbitH-Index: 24
view all 15 authors...
Learners working on major learning projects, such as an undergraduate thesis, frequently engage in information problem solving (IPS). In round-trip IPS, learners set goals and develop a work plan, search for and filter sources, critically analyze and mine key information, and draft and revise a final product. Information problem solving is a prime site for self-regulated learning (SRL) whereby learners formulate and carry out self-designed experiments to improve IPS skills and expand knowledge a...
9 CitationsSource
#1Alyssa Friend WiseH-Index: 26
#2Jovita VytasekH-Index: 8
24 Citations