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Understanding Teacher Use of Technology Michael Russell Damian Bebell Laura O’Dwyer. Research Questions. How is the use of technology impacting teaching and learning? How can districts maximize their investments in technology? What structures promote or obstruct use?
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Understanding Teacher Use of TechnologyMichael RussellDamian BebellLaura O’Dwyer
Research Questions • How is the use of technology impacting teaching and learning? • How can districts maximize their investments in technology? • What structures promote or obstruct use? • How is technology being used for instruction? • How is use of technology affecting learning? • How is use affecting students’ technology fluency?
Vision Leadership Community Resources District Level Physical Infra. Support/Personnel Prof. Devel. Curriculum &Instructional Model Policies and Standards Princ. Beliefs School Leadership School Princ. Preparedness School Culture Home Resource Teacher Beliefs Resources Teacher Preparedness Class Education Students Barriers Use
Vision Leadership Community Resources Physical Infra. Support/Personnel Prof. Devel. Curriculum &Instructional Model Policies and Standards Princ. Beliefs School Leadership Princ. Preparedness School Culture Home Resource Teacher Beliefs Resources Teacher Preparedness Education Students Use Barriers
Methodology • Surveys - District, Principal, Teacher & Student • Site Visits • Case Studies • Student Learning Outcomes
Sample 4 Small Urban 5 Rural 13 Suburban
Linking 92% of Teachers Linked to Principals
Site Visits • 21 Districts • Interview Protocol • Focus on District beliefs and supports • 2 Day: District and 3 Schools • Emergent and thematic coding • Correlation with district survey data
Student Survey Patterns Grade 5
Summary of Student Survey Results • More use at home than in school • Big brother/big sister effect on home use • Use home computers for email, internet, games and chatting • Use home computers for school work • Additionally… • Students are generally confident with their technology skills • Believe they produce good work and learn better when
Quantifying teacher technology use • Develop scales that best explain teacher’s technology use (multi-faceted approach) • Identify those factors that explain or predict each type of technology use
Teacher’s value of technologies 1= very valuable 3= not very valuable
TV/VCR LCD projector All Teachers 1.33 1.63 Teachers without LCD projectors 1.35 1.74 Teachers with LCD projectors 1.25 1.38 Principals 1.32 1.36 Teacher and Principal Values
Teacher Descriptive Stats. 1= never 2= less than once per week 3= once per week 4=three times a week 5= daily
Teacher Descriptive Stats. (2) 1= never 2= once or twice a year 3= several times a year 4=several times a month
Teacher Descriptive Stats. (3) 1= never 2= once or twice a year 3= several times a year 4=several times a month 5= several times a week
Factor analysis (of the above items) When all of the survey items were analyzed… 10 factor solution! Some of it made sense, some did not Beginning point for developing measures/scales of teachers technology of use
Six measures of teacher technology use • Teacher’s Use of Technology for Special Education and Accommodation • Teacher's Use of Technology for Delivery • Teacher’s Use of Email • Teacher’s Use of Technology for Preparation • Teacher-Directed Student Use of Technology • Teacher Use of Technology for Recording Grades
Teacher-directed student use scale SURVEY ITEMS Factor Loading How often do students work individually/using computers 0.841 How often do students work in groups/using computers 0.821 How often do students use computer or portable writing device for writing 0.768 How often do students research/use the internet or CD-ROM 0.762 How often do students use a computer to solve problems 0.672 Percent of variance explained: 60% For example: 5 survey items comprise the teacher-directed student use scale
Relative teacher technology use Teacher technology uses Mean SD Preparation Use of Technology 4.01 .96 Email Use 3.07 1.40 Teacher directed Student Use of Technology 2.68 1.00 Using technology for Grading 2.35 1.60 Technology Use for Delivery 2.30 1.29 Accommodation Use of Technology 1.94 .97 1= never 2= once or twice a year 3= several times a year 4=several times a month 5= several times a week
Building regression models to explain and predict teacher technology use • 29 Independent variables scales developed through exploratory analysis and the literature • These include measures of: • School/District Vision • Teacher Pedagogy • Teacher Philosophy • Leadership • School culture • Technology support • Technology access and distribution • Professional Development + demographic variables
Develop predictor models for each specific type of technology use
Example 1: Using technology for delivery model R 0.438 Adjusted R square 0.190 F 127.45 Significance 0.0001 Predictor Variables Standardized Beta t Significance Teacher’s belief in the importance of computers for teaching scale .233 10.14 0.000 Technology access scale .195 9.71 0.000 Teacher's confidence with technology scale .067 3.03 0.002 Teacher’s belief of using technology to shape classroom use .152 7.53 0.000
Example 2: Technology for professional email use R 0.416 Adjusted R square 0.172 F 122.31 Significance 0.000 Predictor Variables Standardized Beta t Significance Teacher’s belief in the importance of computers for teaching scale .185 9.35 0.000 Technology access scale .188 9.51 0.000 Need for general professional development scale -.155 -8.10 0.000 Teacher’s perception of the district’s technology success .149 7.68 0.000
Specific models for specific uses of technology • Some variables are shared across the different uses • Access to technology • Some variables are more unique • Grade level • Such an approach allows a more detailed way to investigate use
What are Multilevel Techniques? • Ideal for use with data that are nested • students within classrooms • Classrooms within schools • Generalization of OLS regression in which a regression equation is created for each level of data • coefficients refer to specific levels in the data • total variance in outcome is partitioned into within group and between group components
Modeling Outcomes • Partition the variance into its within and between group components • the unconditional model • Add predictors that explain some of the available variance
Teacher Outcomes • Teacher use of technology in the classroom scale • Teacher reported general student use of technology scale • Teacher reported specific application student use of technology scale • Teacher reported student technology products scale • Teacher use of technology for preparation scale • Teacher use of technology for individual student needs scale
Unconditional Model Models • Level 1 Equation • Level 2 Equation
Unconditional Teacher Use Model Summaries
Modeling Teacher Outcomes • Teacher level Model Predictors • Teacher reported obstacles relating to quality of available technology scale • Teacher reported importance of technology for teaching scale • Teacher confidence using computers scale • Teacher attitudes toward teacher directed instruction • Teacher attitudes about the positive impacts of computers • Teacher constructivist beliefs
Modeling Teacher Outcomes School level Model Predictors • School mean student comfort level with technology • School mean student ease of access at home • Principal beliefs about the impact of technology on student work • School mean teacher beliefs about leadership emphasis on technology • School mean teacher beliefs about the quality of available technology • School mean teacher beliefs about the pressure relating to technology use scale • Principals attitude toward teacher directed instruction • School mean teacher beliefs about the school or districts technology vision
Statistical Models • Level 1 Equation • Level 2 Equation