Effizient Lernen, Leben und Arbeitenmit Social Media

Philippe WampflerKantonsschule Stadelhofen, März 2014

phwa.ch/hfgs

Beobachten Sie, wie die Kleinen Däumlinge ihre Handys handhaben, mit den Daumen Knöpfe, Spiele, Suchmaschinen bedienen.

Michel Serres

Mein Vater findet Twitter unmöglich. Er sagt: »Warum würde ich jemandem erzählen wollen, was ich gegessen habe, das ist doch privat?!« Und ich antworte: »Warum sollte ich überhaupt etwas essen, wenn ich nicht jemandem davon erzählen könnte?«

Lena Dunham

Coca-Cola Social Media Guard

USA, 2014 - Quelle: phwa.ch/cocacola

Ablauf

Herausforderung 1

Genuss, Bedürfnisse, Gesundheit

Fear of Missing Out

Philippe Wampfl er | Generation »Social Media« Fear of Missing Out – Diagnose

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Fear of Missing Out – Diagnose

Um zu testen, ob jemand an Fear of Missing Out leidet (vgl. Kapitel 3.11), kann folgender Test ver-wendet werden. Als Antworten werden Zahlen gesetzt. 5 bedeutet »tri! in hohem Maße zu«, 3 »tri! selten zu« und 1 »tri! nicht zu«.

1. Ich habe Angst, die Erfahrungen anderer Menschen seien reichhaltiger und intensiver als meine.

2. Ich habe Angst, die Erfahrungen meiner Freunde seien reichhaltiger und intensiver als meine.

3. Wenn ich bemerke, dass meine Freunde Spaß haben und ich nicht dabei bin, betrübt mich das.

4. Ich werde nervös, wenn ich nicht weiß, was meine Freunde gerade tun.

5. Es ist mir wichtig, die Witze zu verstehen, für die man eingeweiht sein muss.

6. Manchmal frage ich mich, ob ich zu viel Zeit damit verbringe, mich darum zu kümmern, was gerade läu! .

7. Wenn ich eine Gelegenheit verpasse, mich mit meinen Freunden zu tre" en, stört mich das.

8. Wenn ich mit Freunden Spaß habe, ist es mir wichtig, das anderen online mitzuteilen.

9. Wenn ich an einem geplanten Tre" en mit Freunden nicht teilnehmen kann, stört mich das.

10. Wenn ich in die Ferien fahre, verfolge ich, was meine Freunde gleichzeitig tun.

Summe

Auswertung: Liegt ihre Gesamtsumme unter 30, kennen Sie FOMO so, wie das alle Menschen tun. Zwischen 30 und 40 ist ihre Angst leicht verstärkt, bei einer Punktzahl über 40 ist sie deut-lich stärker ausgeprägt.

Tipps: Legen Sie regelmäßig digitale Pausen ein und verbannen sie elektronische Geräte aus Ihrem Schlafzimmer.

Verstärkungseffektwere computed for each participant by averaging across all ten items (M = 2.37, SD = 0.84).

Facebook engagement was measured using a slightly re-worded version of the five items used to measure social media engagement in Study 2. In place of asking about social media use in general,these questions asked about Facebook in particular, during meals (breakfast, lunch, and dinner) and within 15 min of waking and going to sleep. These five values were summed to create one Face- book engagem ent score for each participant (a = .89, M = 11.92,SD = 9.54).

Ambivalent emotional experiences when using Facebook were as- sessed using a brief 10-item version of the PANAS-X (Watson &Clark, 1994 ). Participants used a five point Likert type scale that ranged from 1 = ‘‘not at all’’ to 5 = extremely’’ to rate five positive and five negative emotion adjectives in terms of the extent towhich they experienced each when using Facebook in the past week. Separate positive (a = .85, M = 2.30, SD = 0.78), and negative affect (a = .85, M = 2.30, SD = 0.78), scores were computed for each participant.

Distracted learning was assessed using a single item question that asked participant to report on the number of lectures they used Facebook in during the past week. Participants used a six- point Likert style scale that ranged from 0 = ‘‘No lectures’’ to5 = ‘‘Five lectures’’ to evaluate this item. Although the majority ofparticipants (n = 64) reported they did not use Facebook at all dur- ing lectures, more than a quarter of the sample used Facebook dur- ing class between one and five times (M = 0.52, SD = 1.02).

Distracted driving was measure d using a series of questions ask- ing if they had recently engaged in a set of unsafe behaviors while driving a car. Of the total sample, 71% of participants (n = 62) were regular drivers. These participa nts were instructed to: ‘‘Think back over the past 3 months, how often have you experienced the fol- lowing as a driver?’’ Participants used a four-point Likert style ranging from 1 = ‘‘No’’, 2 = ‘‘Yes, Once or Twice’’, 3 = ‘‘Yes, Occasion- ally’’, 4 = ‘‘Yes Often’’ to respond to four behaviors: ‘‘Texting/emai l-ing and driving’’ (M = 1.38, SD = 0.78), ‘‘Texting/emai ling at light’’(M = 1.76, SD = 0.99), ‘‘Glancing at phone and driving’’ (M = 1.87,SD = 0.92), and ‘‘Glancing at phone at light’’ (M = 2.41, SD = 1.12).Principle components analyses indicated the four items loaded on a single factor, explaining 56.68% of the observed variability,so scores were summed to create one distracted driving score for each participant (a = .84, M = 1.86, SD = 0.78).

4.3. Results

4.3.1. Preliminary analyses There were no main or interacting effects observed between

participant age or gender on the other variables we assessed.

4.3.2. FoMO and Facebook engagement To test the hypothesis that fear of missing out would be posi-

tively related to Facebook engagement we regressed engagement,b = .41, p < .001, onto FoMO scores. Fear of missing out was indeed

related to greater engagement with Facebook at key times in the day.

4.3.3. FoMO and ambivalent emotions when using Facebook To evaluate our prediction that FoMO would be associated with

high levels of ambivalent emotions when using Facebook use weregressed positive affect, b = .31, p < .001, and negative affect,b = .40, p < .001, on FoMO scores. This pattern of relations indicated those high in FoMO were more likely to experienced mixed feel- ings when using social media.

4.3.4. FoMO and distracted learning To test our expectation that FoMO would be associated with the

use of Facebook during university lectures we regressed partici- pant standing on distracted learning, b = .27, p = .013, onto fear ofmissing out scores. This analysis showed that students high inFoMO were more liable to use Facebook during university lectures.

4.3.5. FoMO and distracted driving To evaluate our hypothesis that FoMO would be related to more

frequent use of mobile communications technology when driving we regressed distracted driving scores, b = .28, p = .029, onto FoMO.Young adults who were high in fear of missing out paid greater attention to emails, text messages, and their mobile phones when driving compare d to those lower on FoMO.

5. Discussion

5.1. Summary

Social media utilities have made it easier than ever to know what one’s friends, family, and acquaintances are doing, buying,and talking about. In many ways these social affordances are posi- tive, highlighting opportunities and connectin g people. However,because time is limited, this means people must also miss out ona substantial subset of potential ly rewarding experiences made salient by social media use. This double-edged quality of social media has driven popular interest in and increased speculation about the nature of fear of missing out. Although little is empiri- cally known about fear of missing out at this stage, the present re- search provides a number of insights into how fear of missing out can be reliably assessed and how it constellates with motivatio nal,behavioral , well-being, and demograph ic factors.

In the first study we recruited a large and diverse sample of par- ticipants who rated a pool of items drafted to reflect individua l dif- ferences in fear of missing out. Guided by our considerati on of the extant writings about the phenomenon we pursued an empirica lly rigorous and data-driven approach to create a self-report measure .As a result of strategic item selection and testing we identified ten items that form a new psychometri c instrument to tap into indi- vidual differenc es in FoMO. This first of its kind assessment, the Fo- MOs, is a brief and easy to administer assessment that is sensitive and quantifies FoMO for those who evince low, moderate, and high levels of the fear of missing out construct.

In the second study we collected a larger, nationally representa- tive sample and investigated fear of missing out against the back- drop of SDT, a macro theory of human motivation and extant research exploring motives for social media use. Our goal was toinvestiga te demographic variability in FoMO as well as to under- stand its links to motivational and well-being factors. Results indi- cated that the young, and young males in particular, tended towards higher levels of FoMO. This pair of findings conceptually replicated and lends empirical weight to earlier industry reports (JWT, 2011, 2012 ) that suggested FoMO tends to be a phenomeno ngrappled with by younger people.

Fig. 2. Mediation model.

1846 A.K. Przybylski et al. / Computers in Human Behavior 29 (2013) 1841–1848

Herausforderung 2

Verstehen, warum wir tun, was wir tun

WhatsApp

«Dank der nahezu flächendeckenden Verbreitung von Smartphones in der Schweiz ist Whatsapp jederzeit und überall nutzbar. Dies könne zu einem Erwartungsdruck führen, dauernd kommunizieren zu müssen […] Whatsapp sichtbar, ob jemand online ist oder sogar gerade eine Nachricht schreibt. Verändert sich durch diese virtuelle Transparenz die Kommunikation? Wird der Druck zur Kommunikation stärker?

Prof. Christa Dürscheid

Herausforderung 3

Verstehen, was unsere Geräte tun

Die Rolle von Algorithmen

Herausforderung 4

Resilienz

problematisches Verhalten

problematische Mediennutzung

Herausforderung 5

Schlafen

1. Einschlafzeiten2. Erregung3. Gerätepräsenz4. Nutzung

Herausforderung 6

Konzentration

Sparrow et al., 2011

Das Hirn eines Vogel Strauß‘ ist kleiner als eines seiner Augen.

Gelöscht! Gespeichert! Gespeichert in Ordner X

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 the HMMs were more

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-CPT mean response times in the no-distractors and the distractorsconditions (note that the overall decrease in response times from the nodistractors to the distractors condition is due to greater 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 and HMMs). 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 the HMMs were more

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-CPT mean response times in the no-distractors and the distractorsconditions (note that the overall decrease in response times from the nodistractors to the distractors condition is due to greater 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 and HMMs). 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.

phwa.ch/ophir

Herausforderung 7

Über Probleme sprechen

Herausforderung 8

Den Wert von Geduld lernen

Herausforderung 9

Beziehungen online und offline pflegen

Die virtuelle Berührung kann man nicht gleichsetzen mit tatsächlicher Berührung, mit persönlichen Treffen. Ich tendiere eher dazu zu sagen, dass echte Berührungen dadurch weniger werden. Cem Ekmekcioglu

Herausforderung 10

anders sein als alle anderen

lic. phil. Isabel Willemse Gregor Waller MSc Prof. Dr. Daniel Süss Forschungsschwerpunkt Psychosoziale Entwicklung und Medien Web: www.psychologie.zhaw.ch/JAMES November 2011

Kooperationspartnerin

www.psychologie.zhaw.ch/JAMES

lic. phil. Isabel Willemse Gregor Waller MSc Prof. Dr. Daniel Süss Forschungsschwerpunkt Psychosoziale Entwicklung und Medien Web: www.psychologie.zhaw.ch/JAMES November 2011

Kooperationspartnerin

JAMESfocus 2011 Typologie

7

Unterhaltungs!orientierte

Informations!orientierte

Computerfreaks

Musiker

Analoge

30.8%

24%10.2%

6.2%

28.8%

Informationsorientierten. Die Computerfreaks (10.2%) und die Musiker (6.2%) bilden die kleinsten Gruppen (vlg Abbildung 2).

Abbildung 2: Quantifizierung der Medien- und Freizeittypen Wie oben beschrieben, soll die auf der Basis der JAMES 2010 Daten erstellte Typologie am Datensatz der JAMES-Studie im Jahr 2012 validiert werden. Zusätzlich lassen sich die Typen mit Typologien aus anderen Studien vergleichen, um so Schlüsse bezüglich Gültigkeit der Typologie ziehen zu können. Dabei handelt es sich um die Shell Jugendstudie (Albert, Hurrelmann, & Quenzel, 2010), den Leipziger Lebensstilfragebogen (Beckert-Ziegelschmid & Brähler, 2007), das Dossier «Jugend und Medien» des Verbands SCHWEIZER PRESSE (2008) und die Studie zum Bielefelder Medien-kompetenzmodell von Treumann und Kollegen (2007). Im Folgenden werden kurz Typen aus anderen Studien umrissen und mit den Typen im vorliegenden Bericht verglichen, wobei zu bedenken ist, dass Typisierungen stark abhängig sind von den Variablen mit welchen sie erstellt werden. Lediglich die Typen von Treumann et al. (2007) beinhalten teilweise ähnliche Variablen wie die hier gefundenen Freizeittypen. Ein Vergleich ist daher vor allem Interpretationssache und basiert nicht auf statistischen Ergebnissen.

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Wegen Rolling Stones Konzert: 12

Bewohnerinnen brechen aus Altersheim

aus

Ab 2015 müssen in allen in der EU

verkauften Autos GPS eingebaut sein, damit sie überwacht werden

können.

Der Chefredaktor einer deutschen Zeitung hat das EU-Parlament zwei

Mal gewählt: in Deutschland und Italien

87% aller Schülerinnen und Schüler leiden

unter Schlafstörungen im Unterricht.

Eine Zürcherin hat im Ausgang einen Fremden

geküsst. Darauf bemerkte sie einen Hautausschlag, der laut ihrem Arzt nur beim

Kontakt mit Leichen auftritt.

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Danke!

Folien: Kontakt:

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wampfler@schulesocialmedia.ch+41 78 704 29 29 phwampfler