Yhteisöllisen oppimisen tukeminen mobiililaitteiden avulla:                           ffgfg eri kontekstissa Kolme tapaust...
http://vodpod.com/watch/15508281-alan-kays-dynabook-rare-nhk-video-ipad-1960-1970-lukujen-taitteessa?u=larux&c=mobiililuen...
http://chrome.angrybirds.com/http://www.slideshare.net/philrawcliffe/wac-press-conference-      http://www.tietokone.fi/uu...
http://www.slideshare.net/larux/3-luento-tieto-ja-viestinttekniikan-pedagogiset-perusteet-tietokoneavusteinen-yhteisllinen...
Hutchins, E. (1995). Cognition inthe wild. Cambridge, Mass: MITPress.
2002                                   “His 2002 paper with Roy Pea,                                   "Walk on the Wild S...
Traditional approach / Perinteinen näkökumaMLEARNING – MOBIILIOPPIMINEN.1:1
ONE-TO-ONE TECHNOLOGY  ENHANCED LEARNING           http://www.flickr.com/photos/olpc/303868           0654/         Chan, ...
Future trendULEARNING – U-OPPIMINEN N:1
2008: interpersonal computers                                                                 http://www.slideshare.net/la...
1. AKSELI/1st. axisTANGIBLES,ROOMWARE,PHIDGETS,WEARABLES = ULEARNING/U-OPPIMINEN
1.”U-oppiminen” ”uLearning”Tangibles                                    RoomwareTangibles       http://www.youtube.com/wat...
2. AKSELI/2nd. axisLOCATION BASED MOBILETECHNOLOGIES, MOBILE SOCIAL MEDIA= MLEARNING/M-OPPIMINEN
2. ”mLearning” ”mOppiminen”
Jari LaruYHTEISÖLLISEN OPPIMISENTUKEMINEN MOBIILILAITTEILLA/ SUPPORTING COLLABORATIVELEARNING WITH MOBILE COMPUTERS
AIMS from past to todayThis thesis work focuses on developing and analyzinginnovative ways of supporting applying the fram...
Introduction                                Earli SIGMobile computers                                Everyday contexts Sca...
Collaborative learning, Cognitive tools                               Scaffolding, Structuringidiosyncratic (very   script...
Social patterns in mobile technology mediated collaboration among members of the professional distanceeducation communityT...
Social patterns in mobile technology mediated collaboration among members of the professional distance        education co...
Social patterns in mobile technology mediated collaboration among members of the professional distance        education co...
Social patterns in mobile technology mediated collaboration among members of the professional distance         education c...
Laru, J. & Järvelä, S. (2008). Social patterns in mobiletechnology mediated collaboration among members of theprofessional...
STUDY 2: FLYERS         Laru, J. & Järvelä, S. (2008). Social patterns in mobile         technology mediated collaboration...
Course blog and wiki                                           Mobile applications                                        ...
Figure 5. Pedagogical design of the course. Groups were required to complete a wiki projectby the end of the semester. In ...
Social patterns in mobile technology mediated collaboration among members of the professional distance      education comm...
Monimenetelmäinen (kokeileva) ote            Osatutkimus I                         Osatutkimus II                  Osatutk...
RESULTS
Overall, the analyses revealed nonparticipative behaviour within the onlinecommunity. The social network analysis revealed...
Although the results revealed several shortcomings in the types ofargumentation...….In general, the use of the mobile tool...
In our case, we found that using social software tools together to perform multipletasks likely increased individual knowl...
Social patterns in mobile technology mediated collaboration among members of the professional distance          education ...
Similar  •   Cognitive tools; Generic cognitive tools  •   Mobile computer supported collaborative learning  •   Can be co...
Collaborative learning, Cognitive tools    Scaffolding?                 ?
Collaborative learning, Cognitive tools                               Scaffolding, Structuringidiosyncratic (very   script...
Kiitos / Thank You!QUESTIONS? FEEDBACK?HTTP://WWW.MENDELEY.COM/PROFILES/JARI-LARU/
Yhteisöllisen oppimisen tukeminen mobiililaitteiden avulla: Kolme tapaustutkimusta kolmessa eri kontekstissa
Yhteisöllisen oppimisen tukeminen mobiililaitteiden avulla: Kolme tapaustutkimusta kolmessa eri kontekstissa
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Yhteisöllisen oppimisen tukeminen mobiililaitteiden avulla: Kolme tapaustutkimusta kolmessa eri kontekstissa

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Esitys tilaisuudessa: "Mobiilin oppimisen ja ohjauksen mahdollisuudet ammatillisessa koulutuksessa, mobiiliseminaari 7.12.2011. Helsingin yliopisto"

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Yhteisöllisen oppimisen tukeminen mobiililaitteiden avulla: Kolme tapaustutkimusta kolmessa eri kontekstissa

  1. 1. Yhteisöllisen oppimisen tukeminen mobiililaitteiden avulla: ffgfg eri kontekstissa Kolme tapaustutkimusta kolmessa Mobiilin oppimisen ja ohjauksen mahdollisuudet ammatillisessa koulutuksessa, mobiiliseminaari 7.12.2011. Helsingin yliopisto Jari Laru, yliopisto-opettaja, Oulun yliopisto Jari Laru, University teacher, University of Oulu http://www.mendeley.com/profiles/jari-laru/http://farm4.static.flickr.com/3175/2961226120_61c51497b4_z.jpg?zz=1
  2. 2. http://vodpod.com/watch/15508281-alan-kays-dynabook-rare-nhk-video-ipad-1960-1970-lukujen-taitteessa?u=larux&c=mobiililuento http://www.slideshare.net/larux/1-luento-tieto- ja-viestinttekniikan-perusteet-opintojaksolla-tvt- opetuskytn-historia
  3. 3. http://chrome.angrybirds.com/http://www.slideshare.net/philrawcliffe/wac-press-conference- http://www.tietokone.fi/uutiset/anssi_vanjoki_alypuhelin_kuoleemwc-2011?from=ss_embed
  4. 4. http://www.slideshare.net/larux/3-luento-tieto-ja-viestinttekniikan-pedagogiset-perusteet-tietokoneavusteinen-yhteisllinen-oppiminen-cscl
  5. 5. Hutchins, E. (1995). Cognition inthe wild. Cambridge, Mass: MITPress.
  6. 6. 2002 “His 2002 paper with Roy Pea, "Walk on the Wild Side," has been influential in understanding the future possibilities for wireless handheld learning devices”Roschelle, J., & Pea, R. (2002).A walk on the WILD side: howwireless handhelds maychange CSCL, 51-60.Retrieved fromhttp://dl.acm.org/citation.cfm?id=1658616.1658624
  7. 7. Traditional approach / Perinteinen näkökumaMLEARNING – MOBIILIOPPIMINEN.1:1
  8. 8. ONE-TO-ONE TECHNOLOGY ENHANCED LEARNING http://www.flickr.com/photos/olpc/303868 0654/ Chan, T.-W., Roschelle, J., Hsi, S., Kinshuk, K., BROWN, T., Brown, T., Patton, C., et al. (2006). One-to-one technology-enhanced learning: an opportunity for global research collaboration. Research and Practice in Technology Enhanced Learning, 1(1), 1-26. Retrieved from http://www.worldscinet.com/abstract?id=pii:S1793206806000032
  9. 9. Future trendULEARNING – U-OPPIMINEN N:1
  10. 10. 2008: interpersonal computers http://www.slideshare.net/larux/3-luento-tieto-ja-viestinttekniikan-pedagogiset- perusteet-tietokoneavusteinen-yhteisllinen-oppiminen-cscl http://www.fkaplan.com/file/ca if-interpersonal.docKaplan, F., DoLenh, S., Bachour, K., Kao, G. Y.-ing, Gault, C., Dillenbourg, P.,Huang, J., et al. (2009). Interactive Artifacts and Furniture SupportingCollaborative Work and Learning (Vol. 10, pp. 1-17). Boston, MA: SpringerUS. Retrieved fromhttp://www.springerlink.com/content/uxr3q7t022751275/
  11. 11. 1. AKSELI/1st. axisTANGIBLES,ROOMWARE,PHIDGETS,WEARABLES = ULEARNING/U-OPPIMINEN
  12. 12. 1.”U-oppiminen” ”uLearning”Tangibles RoomwareTangibles http://www.youtube.com/watch?v=5U http://www.youtube.com/watch?v=I5GWUx3ZSMw PiFeJhwS4Phidgets Wearableshttp://www.youtube.com/watch?v=RmLU4GS7zAI http://www.youtube.com/watch?v=4hXM6paYOME
  13. 13. 2. AKSELI/2nd. axisLOCATION BASED MOBILETECHNOLOGIES, MOBILE SOCIAL MEDIA= MLEARNING/M-OPPIMINEN
  14. 14. 2. ”mLearning” ”mOppiminen”
  15. 15. Jari LaruYHTEISÖLLISEN OPPIMISENTUKEMINEN MOBIILILAITTEILLA/ SUPPORTING COLLABORATIVELEARNING WITH MOBILE COMPUTERS
  16. 16. AIMS from past to todayThis thesis work focuses on developing and analyzinginnovative ways of supporting applying the framework ofdistributed scaffolding for learning activities in authenticreal world contexts.In this study theoretical ideas of cognitive tools,collaborative learning and scaffolding are applied fordesigning light-weight mobile software and pedagogicalmodels for learning in authentic real world contexts.This is done in order to generate new knowledge andsolutions that advance collaborative learning in mobilecomputer supported collaborative learning
  17. 17. Introduction Earli SIGMobile computers Everyday contexts Scaffolding collaborative Master’s programme, University, Professional learning with cognitive Community, K-12 students, tools based on Higher Education students, Nature school mobile computers Case I Case II Case III workplace (n=10) Nature (N=22) University (N=22) EMI ILE INTHIG
  18. 18. Collaborative learning, Cognitive tools Scaffolding, Structuringidiosyncratic (very scripted (low stringent (highlittle coercion) coercion) coercion)
  19. 19. Social patterns in mobile technology mediated collaboration among members of the professional distanceeducation communityThe aim of this study was to identify social patterns in mobile technology mediated collaboration among distributed members of theprofessional distance education community. Ten participants worked for twelve weeks designing a master’s programme in InformationSciences. The participants’ mobile technology usage activity and interview data were first analyzed to get an overview of the densityand distribution of collaboration at individual and community levels. Secondly, the results of the social network analyses wereinterpreted to explore how different social network patterns of relationships affect online and offline interactions. Thirdly, qualitativedescriptions of participant teamwork were analysed to provide practical examples and explanations. Overall, the analyses revealednonparticipative behaviour within the online community. The social network analysis revealed structural holes and sparse collaborationamong participants in the offline community. It was found that due to their separated practices in the offline community, they didn’thave a need for mobile collaboration tools in their practices.Laru, J. & Järvelä, S. (2008). Social patterns in mobile technology mediated collaboration among members of the professional distance educationcommunity. Educational Media International Journal, 45(1),17-3. Supporting collaborative inquiry during a biology field trip with mobile peer-to-peer tools for learning: a case study with K-12 learners This study explores how collaborative inquiry learning can be supported with multiple scaffolding agents in a real-life field trip context. In practice, a mobile peer-to-peer messaging tool provided meta-cognitive and procedural support, while tutors and a nature guide provided more dynamic scaffolding in order to support argumentative discussions between groups of students during the cocreation of knowledge claims. The aim of the analysis was to identify and compare top- and low-performing dyads/triads in order to reveal the differences regarding their co-construction of arguments while creating knowledge claims. Although the results revealed several shortcomings in the types of argumentation, it could be established that differences between the top performers and low performers were statistically significant in terms of social modes of argumentation, the use of warrants in the mobile tool and in overall participation. In general, the use of the mobile tool likely promoted important interaction during inquiry learning, but led to superficial epistemological quality in the knowledge claim messages. Laru, J., Järvelä, S. & Clariana, R. (2010). Supporting collaborative inquiry during a biology field trip with mobile peer-to-peer tools for learning: a case study with K-12 learners. Interactive Learning Environments, Online first, 1-15. doi:10.1080/10494821003771350 Supporting small-group learning using multiple Web 2.0 tools: A case study in the higher education context In this single-case study, small groups of learners were supported by use of multiple social software tools and face-to-face activities in the context of higher education. The aim of the study was to explore how designed learning activities contribute to students’ learning outcomes by studying probabilistic dependencies between the variables. The participants (n=22) worked in groups of four to five students for 12 weeks. Groups were required to complete a wiki project by the end of the semester. In order to complete the wiki project, students needed to participate in recurrent solo and collective phases mediated by the use of social software tools and face-to-face meetings in their respective sessions. The data for multivariate Bayesian analysis was composed of video recordings, social software usage activity and pre- and post-tests of students’ conceptual understanding. In our case, we found that using social software tools together to perform multiple tasks likely increased individual knowledge acquisition during the course. Bayesian classification analysis revealed that the best predictors of good learning outcomes were wiki-related activities. In addition, according to the Bayesian dependency model, students who monitored their peers’ work via syndication services and who were active by adding, modifying or deleting text in their group’s wiki obtained higher scores. The model also shows that many other learning activities were indirectly related to learning outcome. Laru, J., Näykki, P. & Järvelä, S. (2011). Supporting small-group learning using multiple Web 2.0 tools: A case study in the higher education context. Special issue on Web 2.0 on Higher Education. Journal of Internet and Higher Education.
  20. 20. Social patterns in mobile technology mediated collaboration among members of the professional distance education community 1. What is the density and the distribution of the collaboration at individual and community levels in the online and offline communities?Questions 2. How do different social network patterns of relationships affect online and offline interactions? 3. How do participants describe teamwork and the technologies used to support it? Supporting collaborative inquiry during a biology field trip with mobile peer-to-peer tools for learning: a case study with K-12 learners 1. What were the differences between top and low performers in regards to collaborative inquiry learning during the field trip? groups? 2. What was the difference between top and low performers in regards to the structural quality of knowledge claim messages? 3. How much did the top and low performers learn about biology during the field trip? Supporting small-group learning using multiple Web 2.0 tools: A case study in the higher education context 1. How much did students learn during the course? 2. Which social software and face-to-face variables were the best predictors for identifying differences between high- and low-performing groups of students? 3. What was the impact of social software and face-to-face sessions on individual students learning gain?
  21. 21. Social patterns in mobile technology mediated collaboration among members of the professional distance education community • 1st generation: mobile versions of desktop tools:Tools FLE3mobile • wlan Supporting collaborative inquiry during a biology field trip with mobile peer-to-peer tools for learning: a case study with K-12 learners • 2nd generation: context- aware peer-to-peer mobile tools: flyers • mobile encounter network (bluetooth) Supporting small-group learning using multiple Web 2.0 tools: A case study in the higher education context • 3nd generation: mobile social media: mobile clients + flickr + wordpress + wikispaces + google reader • 3G connectivity
  22. 22. Social patterns in mobile technology mediated collaboration among members of the professional distance education community • No groups designed (participants worked in three teams though)Design ”Let’s try it” .. • No clear task, work related activities (no formal learning) • Knowledge building • Metacognitive scaffolding Supporting collaborative inquiry during a biology field trip with mobile peer-to-peer tools for learning: a case study with K-12 learners • Dyads/Triads • Ill-structured task • Argumentative collaboration • Procedural scaffolding & metacognitive scaffolding Supporting small-group learning using multiple Web 2.0 tools: A case study in the higher education context • 4-5 students per group • Ill-structured tasks • Small groups of learners were supported by multiple social software tools and face-to-face activities • Recurrent individual and collaborative phases • Multiple scaffolds
  23. 23. Laru, J. & Järvelä, S. (2008). Social patterns in mobiletechnology mediated collaboration among members of theprofessional distance education community. EducationalMedia International Journal, 45(1),17-3.
  24. 24. STUDY 2: FLYERS Laru, J. & Järvelä, S. (2008). Social patterns in mobile technology mediated collaboration among members of the professional distance education community. Educational Media International Journal, 45(1),17-3.
  25. 25. Course blog and wiki Mobile applications Course level tools D. Reflect & E. Review & B.Reflect F. Co-construct Phase: A.Ground C.Conceptualize elaborate evaluate knowledge Course feed Group level tools Software: Collaborative Solo Collaborative Activity: Lecture Discussion Phototaking Blogging Discussion Wikiwork Multiple feeds Merged feeds Monitoring tools G.Monitor Tools used to merge multiple RSS feedsFigure 4. Socio-technological design of the course. The idea of making use of each others’knowledge was operationalized in socio-technical design. It consisted of recurrent individual and collective phases in which studentsused multiple Web 2.0 tools and mobile phones in concert to perform designed tasks. Retrieved from: Jari Laru, Piia Näykki, SannaJärvelä, Supporting small-group learning using multiple Web 2.0 tools: A case study in the higher education context, The Internet andHigher Education, Available online 28 August 2011, ISSN 1096-7516, 10.1016/j.iheduc.2011.08.004.
  26. 26. Figure 5. Pedagogical design of the course. Groups were required to complete a wiki projectby the end of the semester. In order to complete the wiki project, students needed toparticipate in recurrent solo and collective phases mediated by the use of social softwaretools and face-to-face discussions in their respective phases. Jari Laru, Piia Näykki, SannaJärvelä, Supporting small-group learning using multiple Web 2.0 tools: A case study in thehigher education context, The Internet and Higher Education, Available online 28 August 2011,ISSN 1096-7516, 10.1016/j.iheduc.2011.08.004.
  27. 27. Social patterns in mobile technology mediated collaboration among members of the professional distance education community • Quantitative analysis of FLE3mobile’s log-filesMethods SNA Social network analysis • (log file analyzer) Qualitative-Quantitative Interview analysis (SNA analysis) Supporting collaborative inquiry during a biology field trip with mobile peer-to-peer tools for learning: a case study with K-12 learners Mann-whitney • Quantititative Mindmap analysis (pre-post-test) • Qualitative analysis of recorded argumentative U-test • discussions (Mann-whitney U-test) Qualitative analysis of the flyers (Mann-whitney U-test) Supporting small-group learning using multiple Web 2.0 tools: A case study in the higher education context • Quantitative analysis of conceptual knowledge Bayes Classification analysis • test (normalized gain, t-test) Qualitative+Quantitative analysis of social software activities (Bayesian classification Dependency modeling analysis + Bayesian dependency modeling)
  28. 28. Monimenetelmäinen (kokeileva) ote Osatutkimus I Osatutkimus II Osatutkimus III käsitetesti Kyselyt Kyselyt Haastattelut Ryhmähaastattelu Haastattelut Kyselyt Lehtiset Videoidut ryhmätilanteet Logidata (yksi sovellus) Nauhoitetut ryhmätilanteet Keskustelut logidata (useita sovelluksia) käsitekartat onlinedata (wikit, blogit etc) Käsitekarttojen Logidatan analyysi Bayes mallinnus, jonka tilastollinen analyysi, jonka avulla kyselydata, logidata Kevyt keskusteluanalyysi avulla ryhmät jaettiin ja käsitetesti kytkettiin huonosti ja hyvin Verkostoanalyysi (SNA) yhteen [kokeilu] menestyneisiin olemattoman vuorovaikutuksen Verkkoon tuotetun Ryhmätilanteiden ja materiaalin analysointi syiden etsimisessä lehtisten sisällönanalyysi (multilevel IA analysis) Haastattelut tukimateriaalina Mann-Whitney U-test haastatteluiden ja/tai hyvien ja huonojen ryhmätilanteiden ryhmien suoritusten analysointi vertailemiseksiLET - Oppimisen ja koulutusteknologian tutkimusyksikköJari Laru, 22.4.2009 29
  29. 29. RESULTS
  30. 30. Overall, the analyses revealed nonparticipative behaviour within the onlinecommunity. The social network analysis revealed structural holes and sparse collaborationamong participants in the offline community. It was found that due to theirseparated practices in the offline community, they didn’t have a need for mobilecollaboration tools in their practices.
  31. 31. Although the results revealed several shortcomings in the types ofargumentation...….In general, the use of the mobile tool likely promoted importantinteraction during inquiry learning, but led to superficialepistemological quality in the knowledge claim messages.
  32. 32. In our case, we found that using social software tools together to perform multipletasks likely increased individual knowledge acquisition during the course.Bayesian classification analysis revealed that the best predictors of good learningoutcomes were wiki-related activities.
  33. 33. Social patterns in mobile technology mediated collaboration among members of the professional distance education community • Overall, the analyses revealed nonparticipative behaviour within the online community. The social network analysis revealed structural holes and sparse collaboration among participants in the offline community.Results • It was found that due to their separated practices in the offline community, they did not have a need for mobile collaboration tools in their practices. Supporting collaborative inquiry during a biology field trip with mobile peer-to-peer tools for learning: a case study with K-12 learners • Although the results revealed several shortcomings in the types of argumentation, it could be established that differences between the top performers and low performers were statistically significant in terms of social modes of argumentation, the use of warrants in the mobile tool and in overall participation. • In general, the use of the mobile tool likely promoted important interaction during inquiry learning, but led to superficial epistemological quality in the knowledge claim messages. Supporting small-group learning using multiple Web 2.0 tools: A case study in the higher education context • Explorative Bayesian classification analysis revealed that the best predictors of good learning outcomes were wiki-related activities. • In general, the results indicated that interaction between individual and collective actions likely increased individual knowledge acquisition during the course.
  34. 34. Similar • Cognitive tools; Generic cognitive tools • Mobile computer supported collaborative learning • Can be considered as example: development of ”mobile learning” (from past to today) • Design can be considered as example: learning from => learning withDifferent • Study 1 is socio-cultural (COP) while others are socio-cognitive • Methodological designs are quite different • No explicit design cycles from study 1 to study 3, instead studies are independent cases. Development cycles are in design etc.
  35. 35. Collaborative learning, Cognitive tools Scaffolding? ?
  36. 36. Collaborative learning, Cognitive tools Scaffolding, Structuringidiosyncratic (very scripted (low stringent (highlittle coercion) coercion) coercion)
  37. 37. Kiitos / Thank You!QUESTIONS? FEEDBACK?HTTP://WWW.MENDELEY.COM/PROFILES/JARI-LARU/

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