Strategies for Training Teachers - PowerPoint Presentation

1. Strategies for Training Teachers to Integrate Technology in the classroomA systematic reviewSujata N Gamage, gamage@gmail.com (with Amrita Khakurel , Achala Abeykoon, Chivoin Peou,Sandalika Weerasuriya and Tushar Tanwar )ICT4D, Singapore, March 15, 2015This work was carried out with the aid of a grant from the International Development Research Centre, Canada.

2. RESEARCH QUESTION2What makes teachers integrate technology into the teaching–learning process?

3. BACKGROUND3

4. Integration of technology (ICT) in education promised higher learning outcomes4Technology INTERVENTIONStudent learning outcomes (BEFORE)ClassroomStudent learning outcomes (AFTER)

5. Gains are modest but expectations remain high*Cheung, Alan C.K. and Slavin, Robert E. (2013). The effectiveness of educational technology applications for enhancing mathematics achievement in K-12 classrooms: A meta-analysis. Educational Research Review 9 (2013) 88–113.)5Educational technology is making a modest difference in learning of mathematics. It is a help, but not a breakthrough. However, the evidence to date does not support complacency. New and better tools are needed to harness the power of technology to enhance mathematics achievement for all children.”

6. 6“The evidence suggests that teachers went through the motions as prescribed but did not master the innovation in a way that would have allowed students to get the most of it.”Source: RCT by ADB in Costa Rica (2014)Reason: teacher and teaching-learning inside the classroom ignored?

7. What happens inside the classroom black-box?7Technology INTERVENTIONStudent learning outcomes (BEFORE)ClassroomStudent learning outcomes (AFTER)

8. Unpacking the classroom black-box in ICT4ED8Technology INTERVENTIONStudent learning outcomes (BEFORE)Classroom withTeachersStudent learning outcomes (AFTER)Teacher training or support INTERVENTIONSTeacherAcceptance of technology by teacherTechnology using teacher

9. 9Training/support for teachersTeacherAcceptance of technology by teacherTechnology using teacherICT use/integration in the classroom

10. Theory of changeTechnology use OUTCOMES10Teacher training/supportINTERVENTIONSStudent learningOUTCOMES

11. InterventionsBehavioral Perceived usefulness and ease of useNormative Perceptions of those important to youFunctional Training, support, infrastructure & other11SOURCES: Technology acceptance model (TAM), Davis, 1986Theory of planned behavior, Icek Ajzen 1989Unified Theory of Technology Acceptance ad use (UTTAU), Venkatesh, 2003 Technology, Pedagogy & Content (TPACK)Innovation diffusion (Complexity, compatibility, relatedness, observabiity)

12. OutcomesFrequency of useNever to dailyLevel of useTeacher use for preparation/presentation/follow-upTeacher guided student useStudent use for independent learning in or our of classFrequency and level of use12

13. 13POPULATION K-12 in-service teachersINTERVENTION Behavioral Normative Functional CONTROL Experimental (RCTs) Quasi-exptl. (comparables/statistical)OUTCOMES Frequency/Level of useCONTEXT Year, Technology/Use & OtherPICOCs

14. METHOD14

15. SEARCH XYZ databases with specific search string*SCREEN (1) to include empirical studies concerning technology use in K-12 classrooms and exclude all othersSCREEN (2) to include exptl. or Quasi –exptl. studies and exclude all othersEXTRACTION Extract PICOCs for each studyCODING Code predictors/outcomes into few categories as possibleAPPRAISAL Appraise for Risk of bias andSYNTHESIS Calculate effect sizes for category of predictor 15Systematic review process

16. 16Selection biasConfounding variables biasMotivation biasPerformance biasReporting biasType 1/Type II errorsOther biasesTypes of bias

17. RESULTS17

18. 30,000+ hits2000+ empirical studies on technology use in K-12 classroom100+ Quasi experimental [10] Treatment (with or with out comparison group) [90] Natural experiment (with or with out comparison group)Most are observation studies of ICT use employing multivariate regressions to ease out effects of different factors 18Search results (1990-2014)

19. ANALYSIS19Quantitative (~100)Extracting PICOCs and related statisticsEffect size calculationSynthesis (quant.)Qualitative (~100+1900)Extracting PICOCsCodingSynthesis (qualit.)via two linked tracks

20. Improved theory of changeOUTCOMESTechnology use20INTERVENTIONSPECIFIC INTERVENTION(school systems)GENERIC INTERVENTION(Colleges of education, e.g.)BEHAVIORALUsabilityUsefulnessICT proficiency & attitudesPedagogical attitudesNORMATIVESchool policyInfluence by important othersFUNCTIONALSupport from the schoolAvailability of resource, technical support etc.

21. 21Effect size for five intervention categories PERSONALBEHAVIORAL(technological)BEHAVIORAL(pedagogical)NORMATIVEFUNCTIONAL1Abdullah2013-IT knowledgeabilitySMD 2.81--Student attitudes, Ergonomics2Brunk2008Gender, age, advanced degree, exp.Personal computer useSMD 0.85Instructional practicesPoverty, school culture, and principal support.3Fordham 2004Commitment to teachingamount of technology trainingSMD 0.54openness to change--4Hastings 2009 ExperienceProficiency: Productivity SoftwareSMD 0.37Perceived Benefits of Using Technology.---5 Hefernnen 2012Personal use, Self-Efficacy, Playfulness, Skill level SMD 0.39---6Hermans-2008GenderComputer experienceSMD – 0.47General computer attitudesconstructivist beliefs--

22. Working HypothesisNormative/Functional effects > Behavioral effectsIf system-wide intervention such as E-books and IWBs which are integral to the curriculum and test taking are implemented with sufficient support for teachers, negative behavioral attributes of teachers, if any, wont matter 22

23. Thank you23

24. Improved theory of changeOUTCOMESTechnology use24Technology is specifiedBehavioral Usability : Complexity, Trialability and ObservabilityUsefulness: Relatedness, CompatibilityNormativeInfluence by important othersFunctionalResources, Technical support etc.Technology is not specifiedBehavioral ICT skills & attitudesPedagogical skills and attitudes NormativeInfluence by important othersFunctionalResources, technical supportPREDICTORS

25. Extraction worksheet25PaperTechnologyTechnology use outcomesFrequencyLevelBaek_2006(1) none, (2) rarely, (3)Moderate (4) high—almost weekly per semesterTeacher use/student useusing the basic functions of technology,using the enhanced functions of technologyderiving attentionadapting to external requests and others’ expectationsclass preparation and managementrelieving physical fatigue(TEACHER DERIVED)Extractors the factors underlying the lay person implicit ideas or beliefs by surveying the users would provide a more authentic and ecologically valid prospect.Fordham_2004-1 to 5, with participants’ survey responses according toa five-point scale, ranging from “never” to “several times a week.”LOW: Focuses on the teacher using technology to get their job done.MODERATE: Involves teacher facilitation of large group learning activities and studentHIGH: productivity use of technology. Promotes students to be actively engaged in using tech. in individual and collaborative learning activitiesopeness to changeno. of hours of technology trainingno. of hours worked beyond contractual work weekTPCK (Technology factors/Teacher factors); Technology factors (Marcinkiewicz, 1994; Vannatta & O’Bannon, 2002),Hastings_2009TPCK/Tiers of Technologyby Washington State Technology Integration into the Curriculum Working Group (2005).never, less than once per week, once per week, 3 times a week, and daily(1) Teacher-Use of Technology for Delivering Instruction (TUTDI);(2) Teacher-Use of Technology for Class Preparation (T-UTCP) (3) Teacher-Directed Student Use of Technology to Create Products (T-DSUTCP); (4) Teacher-Directed Student Use of Technology during Class Time (T-DSUTCT).Teacher Proficiency: Productivity Software Beliefs and Behaviors about classroom technology use Perceived Benefits of using technologyTPCK/Tiers of Technologyby Washington State Technology Integration into the Curriculum Working Group (2005).Hong_2009TPCK (Teacher/Environment)5-point Likert scale ranging from never to daily useutilization, integration, reorientation, and evolution (Welliver, 1989)Attitude toward computer technology Attitude toward computer technologyComputer literacy skills Hours of teachers’ technology education (10 hours)Number of computers in the classroom AgeTPCK (Teacher/Environment)Johnson_2006TPCK & Welliver’s (1989) Instructional Transformation Model (utilization, integration, reorientation, and evolution).) ‘‘never (1)” to ‘‘daily (7)”.DLE, Communication, Administration, all together (smartschools.be)Years of teaching experience (total model score)Hours of professional development (familiarization) Level of education completed by teachers (reorientation)Teachers’ perception of principals’ knowledge of technology (utilization)TPCK & Welliver’s (1989) Instructional Transformation Model (utilization, integration, reorientation, and evolution).) Pynoo_2011UTAUT0-3 (i.e., never, monthly, weekly, daily).Drill & Practice, Tutorial, Simulation, Instructional Games, Problems Solving, ProductivityEntry, adoption, adaptation, appropriation, and invention Sandholtz (1997)Performance expectancyEffort expectancySocial influenceFacilitating conditionsAcceptance (Attitude, behavioural intention, s-r use)UTAUTRickman_2009'Teacher+Env ('Teacher Personal Attribute + Environmental Variables= Variation in a Teacher’s use of Technology in the K???5 Classroom)developed by van Braaket al. (2004). It consists of six 5-point Likert items(never, every term, monthly, weekly, daily)Supportive use/classroom useTeacher variablesteaching philosophysoftware proficiencysoftware availabilityENV variables not significant'Teacher+Env ('Teacher Personal Attribute + Environmental Variables= Variation in a Teacher’s use of Technology in the K???5 Classroom)Sang_2010The study presents a relational model embracing a wide variety of internal teacher variables related to ICT integration. Building on available research (not UTAUT)Indirect: constructivist beliefs. Perception of ICT policy, Attitudes towards ICt in education, Direct ICT motivation; Supportive use of ICTThe study presents a relational model embracing a wide variety of internal teacher variables related to ICT integration. Building on available research (not UTAUT)

26. 26Data entry & calculationAuthor/Measure of acceptance or use/ Population/ Sample/ Response/ RoBStatistics for Teachers’ skills and attitudes ICT Skills ICT AttitudePedagogy-AttitudeAbdullah-2013Acceptance of E-books (11 items): strongly disagree, disagree, moderate, agree, strongly agree Population: 642 Primary teacher Grade 4—6 in two DUNs representing urban and rural DUNs Sura and Rantau Abang Sample: random sample by school for 5 schools in Sura and 11 in Rantau Abang  Usable Response rate: 254/300 RoB:SelectionConfounding variableIT knowledgeability β; p; t; SE=; Sp; v ; Yt, Yc, Ys; nt =nc = ns =254; SDt, SDc and SDY ; ATT RR: 1.13 (0.01) SMD--

27. 27Summary of effect sizesStudiesPredictors ICT Skills ICT AttitudePedagogy AtitudeAbdullah-2013RoB-LowIT knowledgeabilityRR: 1.13 (0.01) SMDAskar_RoBComplexity RR: SMD- BrunkPersonal computer useRR:SMD-Instructional practicesFordhamamount of technology trainingRR:SMD-openness to changeHermans-2008Computer experienceRR:SMD general computer attitudes constructivist beliefsHong-Table8-p.62Computer efficacyAttitude towars computer technology-HuaTechnology literacy--PynooEffort expectancy--Rickman-tabe 24, p.109Software proficiency-teaching philosophySanford-2007-- Sang-2011Computer motivation-constructivist beliefsSarfo-- Skoertz efficacy for technology integration --Smeets-- Stolsbeliefs about their level of technological proficiencybeliefs about the perceived usefulness-Teo teachers’ computer efficacyTeachers’ attitudes toward computer use -Tondeur-2010-- Tondeur-2010perceived expectancy of success--Van AckerICT skills was in its turn the strongest predictor of self-efficacy.Attitudes towards ICT-Van Braakcomputer experience (computer training, computer experience expressed over time, intensity of computer use)general computer attitudes, attitudes toward computers in education, and technological innovativeness-VanderLindeICT competences-developmental educational beliefsWaight-2014Not significantNot significantNot significantWard-2010confidence in ability to use technology in the classroom, with self-efficacy--Wisenmayer-1999-- Wozney-2006-- Wu-2007-- Ying-Shao-2007-- YucelICT knowledge of teachers--

28. GoalPlots for ICT skills, ICT attitude, Pedagogical attitude, School policy, ICT support (differentiated by technology specificity?); Sample plot below28McEwan, 2014

29. Predictor1: ICT efficacy29PaperDescriptor/DefinitionCodeAbdullah_2013IT KnowledgeabilityAskar_Complexity BrunkLOTI-Personal computer useFordhamamount of technology trainingHermancomputer experience,Hong-Table8-p.62Computer efficacyHuaTechnology literacyPynooEffort expectancyRickmansoftware proficiencySang-2011Computer motivationSkoertz efficacy for technology integration Stolsbeliefs about their level of technological proficiencyTeo teachers’ computer efficacyTondeur-2010perceived expectancy of successVan AckerICT skills was in its turn the strongest predictor of self-efficacy.Van Braakcomputer experience (computer training, computer experience expressed over time, intensity of computer use)VanderLindeICT competencesWard-2010confidence in ability to use technology in the classroom, with self-efficacyYucel'ICT knowledge of teachers

30. Theory of Planned behavior Icek Ajzen (2006)30

31. Unified theory on technology acceptance and useUTTAU (Venkatesh , 2003)31