Visualizing Narrative Structures and Learning Style Information in Personalized e-Learning Systems

Williams, F. Peter; Conlan, Owen

doi:10.1109/icalt.2007.282

Cited by 10 publications

(13 citation statements)

References 5 publications

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“…Related Work Performance: Grades on assignments, cumulative performance on problems for a particular concept [1,6,15,17,18] Access and Activity Patterns: What, how much, and when content has been opened, how long a student stays on a piece of content, student navigational path through the content, when a student turned in an assignment [1,2,6,8,11,12,15,17,18,20] Forum Discussions: Author of a post, when the post was made, structure of follow-up posts, how many posts a student made, how many follow-up posts are in threads each student made, number of posts read by a student [7,8,15,17,18] Student Demographics: Location, reason for taking the course, age, learning style [12,20] 3. By and large, MOOC instructors want the same sources of information as instructors of smaller-scale distance learning courses, as evoked by earlier surveys.…”

Section: Information Visualizedmentioning

confidence: 99%

“…Standard graphs used by prior work [1,2,6,8,11,12,15,17,18,20] [12] e-learning tracking visualizations allow filtering by time and any subset of students. It also incorporates an understanding of course hierarchy, which provides an ability to drill down through this hierarchy.…”

Section: Visualizations Of Student Informationmentioning

confidence: 99%

“…Evaluation by prior work mainly involved interviews and focus groups [7,11,15,17,18,20] and usually reported a mix of both positive responses to the system and a need for future improvements. Three prior works did not include an evaluation section [2,8,12].…”

Section: Visualizations Of Student Informationmentioning

confidence: 99%

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Monitoring MOOCs

Stephens-Martinez

Hearst

Fox

2014

Proceedings of the First ACM Conference on Learning @ Scale Conference

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For an instructor who is teaching a massive open online course (MOOC), what is the best way to understand their class? What is the best way to view how the students are interacting with the content while the course is running? To help prepare for the next iteration, how should the course's data be best analyzed after the fact? How do these instructional monitoring needs differ between online courses with tens of thousands of students and courses with only tens? This paper reports the results of a survey of 92 MOOC instructors who answered questions about which information they find useful in their course, with the end goal of creating an information display for MOOC instructors. The main findings are: (i) quantitative data sources such as grades, although useful, are not sufficient; understanding the activity in discussion forums and student surveys was rated useful for all use cases by a large majority of respondents, (ii) chat logs were not seen as useful, (iii) for the most part, the same sources of information were seen as useful as found in surveys of smaller online courses, (iv) mockups of existing and novel visualization techniques were responded to positively for use both while the course is running and for planning a revision of the course, and (v) a wide range of views was expressed about other details.

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Section: Information Visualizedmentioning

confidence: 99%

Section: Visualizations Of Student Informationmentioning

confidence: 99%

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Monitoring MOOCs

Stephens-Martinez

Hearst

Fox

2014

Proceedings of the First ACM Conference on Learning @ Scale Conference

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“…Naudojant VMA sukauptus studentų veiklos duomenis bei pritaikius duomenų gavybos metodus -grupavimą (klasterizavimą), klasifi kavimągalima identifi kuoti studentus pagal mokymo būdą, stilių (Liu & Shih, 2007), skirti juos prie atitinkamos grupės ir pateikti pasiūlymus kurso kuratoriui, kaip parinkti kiekvienam studentui tinkamiausią mokymo metodą bei pateikti pritaikytą konkrečiam asmeniui mokymo medžiagą (Williams & Conlan, 2007).…”

Section: Studentaiunclassified

Nuotolinių studijų vartotojų poreikių analizė

Sakalauskas¹,

Preidys²

2009

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Nuotolinės studijos šiuo metu tampa viena populiariausių studijų formų Lietuvoje ir pasaulyje. Besivystant informacinėms ir komunikacinėms technologijoms daugelis žmonių studijuoja neatsitraukdami nuo savo darbo vietų. Tokiame studijų procese dalyvauja skirtingi vartotojai: studentai, dėstytojai, nuotolinių modulių kūrėjai, auditoriai, virtualaus mokymo aplinkų administratoriai. Straipsnyje analizuojamos atskiros vartotojų grupės, šių grupių atstovų poreikiai studijuojant nuotoliniu būdu ir tųporeikių tenkinimo būdai.The Analysis of Distance Education Users NeedsLeonidas Sakalauskas, Saulius Preidys SummaryDifferent users are participating in distance learning process: teachers (tutors), distance course creators, auditors, VLE administrators. The quality of such studies depends on all of these groups: module developed qualitatively will be convenient for the learner and helpful for the tutor. All the study process depends on the administrator’s activities: if server is working with breaks, studies can become unpredictable and not attractive. In this article the needs of different user groups are analysed and conditions are created for the programming agent development which can improve distance education process.ight: 18px;">

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“…Third, learning environments must also be accessible. For example, Williams and Conlan (2007) would counteract cognitive accessibility problems by providing a means whereby users can visualize the complex space in which they are learning. In fact, accessibility problems can be found at any of the nine components of human information processing presented by Simplex Two (see above).…”

Section: Technology-enhanced Learning Environmentsmentioning

confidence: 99%