Media Literacy and Civic Engagement in the Context of Ability Grouping
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Media Literacy and Civic Engagement in the Context of Ability Grouping

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Renee Hobbs and Hans Martens report research about media literacy and civic engagement in the context of ability grouping in a U.S. high school. Presentation at Digital Media and Learning Conference, ...

Renee Hobbs and Hans Martens report research about media literacy and civic engagement in the context of ability grouping in a U.S. high school. Presentation at Digital Media and Learning Conference, San Francisco, March 3, 2012.

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Media Literacy and Civic Engagement in the Context of Ability Grouping Media Literacy and Civic Engagement in the Context of Ability Grouping Presentation Transcript

  • Renee Hobbs Exploring Media Literacy and University ofCivic Engagement in the Context of Rhode Island USA Ability Grouping in High School Hans Martens University of Antwerp, Belgium
  • Montgomery BlairHigh SchoolSilver Spring,Maryland2750 students335 teachersTwo specializedprograms andseven academies,containing a totalof 15 academicdepartments.
  • How do differenttypes of medialiteracy educationprograms impactstudents’knowledge,analysis skills andcivic engagement?
  • Selective Admission Programs Communication Arts Program (CAP)Science, Mathematics and Computer Science Open Admission Programs Media Literacy Entrepreneurship International Studies and Law Human Service Professions Science, Math and Technology
  • Communication Arts Program (CAP) A selective admission 4-year program that integrates the humanities, media analysis and production, now in its 25th year
  • Media Literacy Academy Two stand-alone social studies courses in Media Literacy and Media and Society
  • Research DesignQuasi-experimental study2 x 2 factorial Media Literacy ML ACADEMY CAP Treatment CONTROL CONTROL No ML Ability Grouping Open Selective Admission Admission
  • Respondents identify how much they use theMEASURES Internet on an 8-point scale ranging from never to every day.Internet useInformation Motives (U&G)Civic EngagementNews AnalysisAd AnalysisMedia Knowledge
  • To assess students’ motives to seek outMEASURES information as a part of daily life, students were asked to respond to four statements:Internet use • I use the internet to search for informationInformation Motives (U&G) • to see what is out there • to keep up with current events and issuesCivic Engagement • because it provides me with a new and interesting way to do researchNews AnalysisAd AnalysisMedia Knowledge
  • Students were asked to report if they expect toMEASURES engage in the following activities when they become an adult:Internet use • vote in national electionsInformation Motives (U&G) • get information about candidates before voting in an electionCivic Engagement • join a political party • write letters to a newspaper about social orNews Analysis political concerns • be a candidate for a local or city officeAd Analysis • volunteer time to help poor or elderly people in the communityMedia Knowledge • collect money for a cause • collect signatures for a petition • participate in a peaceful rally or protest. A 4-point scale was used, scaled as certainly will not do, probably will not do, probably will do, and certainly will do.
  • In the news analysis task, students read a shortMEASURES Time magazine piece and responded to open- ended questions including:Internet use • summarize the main point of the articleInformation Motives (U&G) • identify the target audience & explain what specific information from the readingCivic Engagement supports your answer • identify the message purposeNews Analysis • identify what techniques were used to attract and hold attentionAd Analysis • list some different points of view presented • Identify omitted informationMedia Knowledge Scores were summed to form an additive index which ranged from 14 to 0.
  • In the ad analysis task, students were given a printMEASURES ad and asked to respond to open-ended questions including:Internet use • identify the target audience & explain whatInformation Motives (U&G) specific information from the reading supports your answerCivic Engagement • identify the message purpose • Identify the ad’s implied message or subtextNews Analysis • identify what techniques were used to attract and hold attentionAd Analysis • list some different points of view presented • Identify omitted informationMedia Knowledge Scores were summed to form an additive index which ranged from 14 to 0.
  • Students completed a short test relating toMEASURES different facets of the media industry, including information about history, economics, institutions, audiences andInternet use effects.Information Motives (U&G) MULTIPLE CHOICE (6 items):Civic Engagement • identify the main purpose of photos in a newspaperNews Analysis • recognize the most common kind of economic control over mass media • name the system of financing used to pay forAd Analysis commercial radio. TRUE FALSE (11 items)Media Knowledge • The number of companies that own mass media outlets is growing • Newspapers make most of their money through the price paid by the consumers who buy them
  • Data AnalysisComparison of means Table 1 Comparing means Open Admission Program Selective Admission Program Other program ML program Other program ML program Mean (SD) Mean (SD) Mean (SD) Mean (SD) Media knowledge .53 (.17) .62 (.22) .71 (.17) .75 (.13) News analysis 4.80 (3.09) 4.27 (3.32) 7.60 (3.16) 8.86 (2.58) Ad analysis 8.20 (3.45) 8.38 (4.02) 9.31 (3.18) 11.10 (3.16) n = 191 n = 55 n = 87 n = 59There are gaps between Open Admission and Selective Admission students Students in Open Admission ML program are least skilled at news analysis Students in Selective Admission ML program are most knowledgeable about media and most skilled at both news and advertsing analysis
  • Data AnalysisCorrelation matrix Table 2 Correlation Matrix 1 2 3 4 5 6 7 8 1. Civic engagement 1 2. Gender (female) .25** 1 3. Academy level .11* -.02 1 4. ML program .19** .24** .19** 1 5. Internet use -.17** -.02 -.28** -.03 1 6. Information motive .23** .04 .17** .03 -.34** 1 7. Media knowledge .19** -.05 .43** .23** -.17** .08 1 8. News analysis .27** .20** .48** .13* -.23** .13** .30** 1 9. Ad analysis .16** .20** .24** .16* -.08 .08 .25** .50** Note: all tests are two-tailed. *p < .05, **p <.01. Ability grouping is related to information motives, media knowledge, news analysis and ad analysis
  • Data AnalysisCorrelation matrix Table 2 Correlation Matrix 1 2 3 4 5 6 7 8 1. Civic engagement 1 2. Gender (female) .25** 1 3. Academy level .11* -.02 1 4. ML program .19** .24** .19** 1 5. Internet use -.17** -.02 -.28** -.03 1 6. Information motive .23** .04 .17** .03 -.34** 1 7. Media knowledge .19** -.05 .43** .23** -.17** .08 1 8. News analysis .27** .20** .48** .13* -.23** .13** .30** 1 9. Ad analysis .16** .20** .24** .16* -.08 .08 .25** .50** Note: all tests are two-tailed. *p < .05, **p <.01. Participation in a ML program is positively related with media knowledge, news analysis and advertising analysis
  • Data AnalysisCorrelation matrix Table 2 Correlation Matrix 1 2 3 4 5 6 7 8 1. Civic engagement 1 2. Gender (female) .25** 1 3. Academy level .11* -.02 1 4. ML program .19** .24** .19** 1 5. Internet use -.17** -.02 -.28** -.03 1 6. Information motive .23** .04 .17** .03 -.34** 1 7. Media knowledge .19** -.05 .43** .23** -.17** .08 1 8. News analysis .27** .20** .48** .13* -.23** .13** .30** 1 9. Ad analysis .16** .20** .24** .16* -.08 .08 .25** .50** Note: all tests are two-tailed. *p < .05, **p <.01. Frequency of Internet use is negatively related with information motive, media knowledge, news analysis, and ad analysis
  • Data AnalysisMultiple regression Table 3 Predictors of civic engagement Model 1 B SE β Intercept 2.23 .09 Gender (Female) .24 .05 .23*** Academy level .09 .05 .08 ML program .13 .06 .11* Internet use Information motive Media knowledge News analysis Ad analysis Total R² = .17. For model 2, ∆R² = .09. *p < .05, **p <.01, ***p <.001. After controlling for gender and ability grouping, participation in a ML program independently contributes to civic engagement
  • Data AnalysisMultiple regression Table 3 Predictors of civic engagement Model 1 Model 2 B SE β B SE β Intercept 2.23 .09 1.51 .19 Gender (Female) .24 .05 .23*** .20 .05 .20*** Academy level .09 .05 .08 -.11 .06 -.10 ML program .13 .06 .11* .09 .06 .08 Internet use -.02 .02 -.04 Information motive .12 .03 .18*** Media knowledge .44 .15 .16** News analysis .03 .01 .20** Ad analysis -.01 .01 -.04 Total R² = .17. For model 2, ∆R² = .09. *p < .05, **p <.01, ***p <.001. After controlling for gender, ability grouping, and ML program, information motive, media knowledge and news analysis all contribute to civic engagement
  • WE LEARNED: Ability grouping emerges from the needs andcompetencies of teaching staff, administrative priorities andcommunity values
  • WE LEARNED :Media literacy programs activate civic engagementdespite differences in instructional practices and the characteristicsof the student body
  • WE LEARNED: Intellectual curiosity and knowledge about themedia are associated with news analysis and civic engagement
  • WE LEARNED : Information-seeking motives, not time spentonline, is associated with media literacy and civic engagement
  • Renee Hobbs Exploring Media Literacy and University ofCivic Engagement in the Context of Rhode Island USA Ability Grouping in High School Hans Martens University of Antwerp, Belgium