SeLC 2015 - Keynote Wampfler

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  • entlichkeitsarbeit von Schulenund Social Media

    Philippe WampflerBrunnen, 9. April 2015phwa.ch/brunnen

    Generation Y beim Lernen begleiten Keynote SeLC Philippe Wampfler - phwa.ch/selc

  • Ablauf

  • Teil 1Mediennutzung der Generation Y

  • Axiom Jugendliche nutzen Medien nicht wie

    Erwachsene das a) denken

    b) mchten

  • 1.Resultat, nicht Prozess

    Bild: Samkit Shah

  • Praxisbezug

  • 2.Jugend- vs. Generationenverhalten

  • 74 5.3 Internet = Facebook?

    Facebook vs. WhatsApp der Reiz des Neuen?

    Ob WhatsApp Facebook zuknftig den Rang ablaufen wird, kann hier nicht beantwortet werden.Fest steht allerdings, dass WhatsApp anders gelagerte Kommunikationsbedrfnisse der jungen Menschen erfllt. WhatsApp dient vor allem der (tages)aktuellen und direkten Kommunikation undwird dementsprechend hufiger als Facebook fr Verabredungen, Gesprche ber private Nachrichtenund das Versenden von Fotos genutzt. Aktivitten, die hufiger bei Facebook als bei WhatsApp statt-finden, sind demgegenber eher ungerichtet d. h. sie wenden sich nicht ausschlielich an einen bestimmten Empfnger und deutlicher asynchron, d. h. es erfolgt keine direkte zeitliche Reaktionauf einen Kommunikationsimpuls.

    80

    90Prozent

    70

    50

    60

    40

    30

    20

    10

    09 11 13 15 17 19 10 12 14 16 18 20 21 22 23 24 Jahre

    Basis: 1.500 Flle; 9- bis 24-Jhrige

    Wie hufig nutzt Du die folgenden Online-Angebote?

    WhatsApp, tglich

    Grafik 42

    Gesamt24-Jhrigrige

    Ges WeiblichWei MnnlichMn

    Altersspezifische Nutzung von WhatsApp

    715.3 Internet = Facebook?

    WhatsApp wird zum wichtigen Kommunikationskanal online

    Neben Facebook hat sich in krzester Zeit auch der Messaging-Dienst WhatsApp zum tglichenBegleiter und wichtigen Kommunikationsmittel entwickelt41 vor allem fr die Jugendlichen ab 14 Jahren. Die App dient dem synchronen Austausch von Nachrichten, Ton- und (Bewegt-)Bildmate-rial oder auch Links zwischen Personen, die ihre Kontakte gegenseitig im Telefonbuch abgespeichertund die App ebenfalls installiert haben, bzw. auch innerhalb von Gruppen. Auch mit WhatsApp befindensich die Nutzer dauerhaft in Chat-Konversationen. Weil dieser Kommunikationskanal stndig aufEmpfang ist, haben viele Jugendliche und junge Erwachsene, wie weiter oben erlutert, den Eindruck,stndig online zu sein. Die quantitative Befragung zeigt, dass der Messaging-Dienst nach Facebookund Google mittlerweile die drittwichtigste Internet-Anwendung fr Jugendliche ab 14 Jahren gewordenist: Mehr als ein Drittel der Jugendlichen und jungen Erwachsenen hat das Gefhl, dass WhatsAppunentbehrlich fr die alltgliche Kommunikation geworden ist.

    80

    90Prozent

    70

    50

    60

    40

    30

    20

    10

    09 11 13 15 17 19 10 12 14 16 18 20 21 22 23 24 Jahre

    Basis: 1.500 Flle; 9- bis 24-Jhrige

    Wie hufig nutzt Du die folgenden Online-Angebote?

    Facebook, tglich

    Grafik 39

    Gesamt24-Jhrigrige

    Ges WeiblichWei MnnlichMn

    Facebook: Altersspezifische Nutzung

    41 WhatsApp Inc. wurde 2009 in Santa Clara, Kalifornien von Diana Chub gegrndet und ist seit 2010 auch in Deutschlandverfgbar. Erstmals im Juni 2013 verffentlichte das Unternehmen aktuelle Nutzerzahlen im Wall Street Journal, wonachWhatsApp 250 Mio. Nutzer weltweit haben soll. Im August wurden zudem 20 Mio. Nutzer in Deutschland gegenber demUS-Blog AllThingsD besttigt: http://allthingsd.com/20130806/the-quiet-mobile-giant-with-300m-active-users-whatsapp-adds-voice/

  • 3. Aufmerksamkeitskonomie

  • 90-9-1-Regel

    Quelle: alike.ch

  • 4.Youtube-Medienwelt

  • 5.Selfies verstehen

  • 6.digital nativesdigital sozialisiert

    Bild: bandt.com.au

  • digitaler Dualismus

  • problematisches Verhalten

    problematische Mediennutzung

  • Die Angst, etwas zu verpassenFOMO

    GrundbedrfnisseAutonomieKompetenz

    Geliebt-Werden

  • 7.private von schulischer Kommunikation trennen

  • Filtersouvernitt

  • 8.traditionelle vs. neue

    Konzentration

  • X-probe was presented, and participants had to refer to the cuethey maintained in the face of distractors (AX and BX trials):HMMs were 84 ms slower than LMMs to respond to AX trials,t (28) ! "3.27, P # 0.003, and 119 ms slower to respond to BXtrials, t (28) ! "3.25, P # 0.003, yielding a significant LMM/HMM status*presence of distractors interaction, F (1, 28) !5.21, P # 0.03. These data replicate the results from the filtertask, again demonstrating that HMMs are less selective inallowing information into working memory, and are thereforemore affected by distractors. As target trials comprised 70% of all trials in the standard

    version of the AX-CPT, the task was also indicative of theparticipants ability to withhold prepotent responses, i.e., theirability to withhold a target response on the relatively rare BX orAY trials, each of which constituted only 10% of trials. The lackof significant differences between the groups, reinforced by theabsence of a group difference on the Stop-Signal task (15), t(37)!"0.15, P$ 0.88, suggests that the two groups do not differin their level of response control.

    Filtering Irrelevant Representations in Memory: Two- and Three-BackTasks. In the two- and three-back tasks (16), which examine themonitoring and updating of multiple representations in workingmemory, HMMs showed a significantly greater decrease inperformance (d%) from the two- to the three-back task;task*HMM/LMM status interaction, F (1, 28) ! 4.25, P # 0.05.Interestingly, although both groups showed similar decreases inhit-rates (the number of targets correctly identified) from thetwo-back to the three-back task, F (1, 28) ! 0.14, P $ 0.72 (Fig.3A), HMMs showed a greater increase in their false alarm rate(the number of nontargets incorrectly marked as targets), F (1,28) ! 5.02, P # 0.03 (Fig. 3B). This effect was driven by targetletters that had previously appeared during the task, but wereoutside the range participants were instructed to hold in mem-ory. Specifically, in the three-back task, HMMs were more likelyto false alarm to letters that had more previous appearances, F(1, 13)! 6.31, P# 0.03. This indicates that theHMMsweremore

    Fig. 1. The filter task. (A) A sample trial with a 2-target, 6-distractor array.(B) HMM and LMM filter task performance as a function of the number ofdistractors (two targets). Error bars, SEM.

    Fig. 2. AX-CPTmean response times in the no-distractors and the distractorsconditions (note that the overall decrease in response times from the nodistractors to thedistractors condition is due togreater predictability of probeonset as a result of the rhythmic nature of the distractors; the key data pointis the difference in the distractors condition between LMMs andHMMs). Errorbars, SEM.

    Fig. 3. Two- and three-back task results. (A) Hit rates. (B) False alarm rates.Error bars, SEM.

    15584 ! www.pnas.org"cgi"doi"10.1073"pnas.0903620106 Ophir et al.

    Multitasking

    X-probe was presented, and participants had to refer to the cuethey maintained in the face of distractors (AX and BX trials):HMMs were 84 ms slower than LMMs to respond to AX trials,t (28) ! "3.27, P # 0.003, and 119 ms slower to respond to BXtrials, t (28) ! "3.25, P # 0.003, yielding a significant LMM/HMM status*presence of distractors interaction, F (1, 28) !5.21, P # 0.03. These data replicate the results from the filtertask, again demonstrating that HMMs are less selective inallowing information into working memory, and are thereforemore affected by distractors. As target trials comprised 70% of all trials in the standard

    version of the AX-CPT, the task was also indicative of theparticipants ability to withhold prepotent responses, i.e., theirability to withhold a target response on the relatively rare BX orAY trials, each of which constituted only 10% of trials. The lackof significant differences between the groups, reinforced by theabsence of a group difference on the Stop-Signal task (15), t(37)!"0.15, P$ 0.88, suggests that the two groups do not differin their level of response control.

    Filtering Irrelevant Representations in Memory: Two- and Three-BackTasks. In the two- and three-back tasks (16), which examine themonitoring and updating of multiple representations in workingmemory, HMMs showed a significantly greater decrease inperformance (d%) from the two- to the three-back task;task*HMM/LMM status interaction, F (1, 28) ! 4.25, P # 0.05.Interestingly, although both groups showed similar decreases inhit-rates (the number of targets correctly identified) from thetwo-back to the three-back task, F (1, 28) ! 0.14, P $ 0.72 (Fig.3A), HMMs showed a greater increase in their false alarm rate(the number of nontargets incorrectly marked as targets), F (1,28) ! 5.02, P # 0.03 (Fig. 3B). This effect was driven by targetletters that had previously appeared during the task, but wereoutside the range participants were instructed to hold in mem-ory. Specifically, in the three-back task, HMMs were more likelyto false alarm to letters that had more previous appearances, F(1, 13)! 6.31, P# 0.03. This indicates that theHMMsweremore

    Fig. 1. The filter task. (A) A sample trial with a 2-target, 6-distractor array.(B) HMM and LMM filter task performance as a function of the number ofdistractors (two targets). Error bars, SEM.

    Fig. 2. AX-CPTmean response times in the no-distractors and the distractorsconditions (note that the overall decrease in response times from the nodistractors to thedistractors condition is due togreater predictability of probeonset as a result of the rhythmic nature of the distractors; the key data pointis the difference in the distra