Preliminary Exam

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Presents justification for dissertation study looking at five different types of learner-content interaction in self-directed electronic professional development in science education

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  • National Assessment of Education Progress (NAEP) measures grades 4, 8 and 12. Scores in science nearly stagnant for last 30 years across all grade levels. Proficient: Solid academic performance and demonstrated competency of challenging subject matter. Trends in International Mathematics and Science Study (TIMSS): We did score significantly higher then overall average score of 500. Organization for Economic Cooperation and Development (OCED): Programme for International Student Assessment (PISA)-41 nations with 275,000 students. In math near bottom. In 2006 PISA focus on science, environmental science for 15 year olds. Not just recall/recognition, but open constructed responses apply conceptual understanding.
  • Horizon: NSF-sponsored national survey over 5,700 science and mathematics educators. Ingersol: Assigned to teach in science area with little formal training. Over 40% in physical science classes are taught by someone with neither a major nor minor in chemistry, physics or earth science. Given teacher attrition and migration (revolving door), high poverty schools taught by less qualified teachers as seek better teaching assignments. Small private schools highest Out of Field. Leave profession prematurely (within first 3 years, low pay, inadequate support, student discipline, little input into school decision making). Alternative certification increasing recruitment not solve shortage if not address these issues.
  • Appears to support need for science PD at upper elementary and middle levels. NSDC report pulled data from 2003-2004 NCES Schools and Staffing Survey 23% of teachers listed content-related PD as most common need. 83.4% of teachers engaged in PD focused on content they teach, but not sufficient depth (16 hours/yr)
  • Dede et al. (2006): Elmore (2004): Loucks-Horsley (1999): US Dept Ed (2009): Sloan Consortium (2008): Asbell-Clarke et al. (2007): Banilower et al. (2007): Dede et al. (2009): Garet et al. (2001): Yoon et al. (2008):
  • Dede et al. (2006): Elmore (2004): Loucks-Horsley (1999): US Dept Ed (2009): Sloan Consortium (2008): Asbell-Clarke et al. (2007): Banilower et al. (2007): Dede et al. (2009): Garet et al. (2001): Yoon et al. (2008):
  • Getting the mix right again: An updated and theoretical rationale for interaction. Internal Review of Research in Open and Distance Learning. 4 (2). 2003.
  • Anderson (2003):Getting the mix right again: An updated and theoretical rationale for interaction. Internal Review of Research in Open and Distance Learning. 4 (2).
  • del Valle et al. (2009): Looked at learners with on-demand access to course modules noticed three categories of users through cluster analysis: (a) mastery (experienced), (b) task focused, (c) minimalist/procrastinator. Looks at click-stream footprints (where go, how frequent access, how long stay between clicks, total sessions, course duration, proportion of resources accessed, etc.), in addition to satisfaction, perceived learning and transfer and group learning preference. Procrastinator preferred working as group, Task-focused did not, and Mastery mid-point, but leaned to individually paced learning. Rhodes (2009): Explore preferences of self-paced learners applying Anderson’s interaction equivalency theory (10 adult learners. Support Paulsen’s (1993) Theory of Cooperative Freedom, which argues that many students who choose a distance learning format do so in search of freedom from not only the time and place learning constraints, but also freedom to choose the type of media and content, times of access, and pace of the learning. Participants unanimously noted that the unique self-paced format was a pivotal factor enabling them to enroll in an online program of study. Such responses give credence to the call for flexible and emergent learning designs that meet the needs of an ever-changing adult learner population. Blogging and bookmarking tools well received. Instructor and content equally important in self-paced. Walker et al. (2008): Six e-learning modules in various topics, reading, writing, Whitaker et al (2007): Dede studies: 235 pre-K teachers provided resources, three level of “content packages and services”. Group 1: iBook and limited web access-no required use, Group 2: iBook, full web access and print materials, support tools, videos through web site, encouraged to use. Group 3: Same as two, with web-cam for conferencing, and feedback on their own VHS video lessons mailed in. Found about 213 logged onto web site over 6 month period (21 logins per user). Consultancy grouped (with their own videos), logged on significantly more then other two groups. Materials Group 1 (most time during each visit—not print materials), but far less visits compared to web and consutlancy groups (groups 2 and 3). Study found level of support received affects level of participation.
  • Asbell-Clarke (2007): 40 courses, 35 instructors across 6 institutions, 250 students. 55% use books 1-3+ times/week. Hands on (1-2 per course). Call for more hands-on and LO’s Harlen and Doubler (2004): Online and f2f course in science content and inquiry (15 and 18 N respectively). Inquiry and investigations most valuable, online spent more time, higher confidence, learned more, little change in certain areas of inquiry as seen in pre/post definition and final lesson plan. Content: Properties of matter and changes in matter. Owsten et al. (2006): 33 science teachers. Online requested reflective posting to journal articles (not sharing/discussing student work like Berger). Difficult to share online with strangers, not rich/immediate feedback to their postings online Berger et al. (2008): Goal to design PD that move from 9 once-month PD experiences to 9 month PD experience. Achieved online through reflective tools, building off teachers comments and student comments/work. (Your comments, Hot Polls, Hot Reports, Smashing Sentences, Mini-research). Content was KIR (Knowledge Integration Routine) for students: Individual work-group work-class work-homework-individual reflection (facilitates conceptual learning). Krall et al. (2009): 43 teachers grade 4-8 from Appalacia (KY). 30-40 hour online short course. Significant gains for 81.4% of teachers in six of 9 science concept topics (temperature/heat). Rated kits and investigations most high, then CD-ROM at 68%. Some teachers formed cohorts if geographically close to each other to work through and discuss experiments. Email support ranked lowest, compared to teacher journals.
  • Asbell-Clarke (2007): 40 courses, 35 instructors across 6 institutions, 250 students. 55% use books 1-3+ times/week. Hands on (1-2 per course). Call for more hands-on and LO’s Berger et al. (2008): Goal to design PD that move from 9 once-month PD experiences to 9 month PD experience. Achieved online through reflective tools, building off teachers comments and student comments/work. (Your comments, Hot Polls, Hot Reports, Smashing Sentences, Mini-research). Content was KIR (Knowledge Integration Routine) for students: Individual work-group work-class work-homework-individual reflection (facilitates conceptual learning). Harlen and Doubler (2004): Online and f2f course in science content and inquiry (15 and 18 N respectively). Inquiry and investigations most valuable, online spent more time, higher confidence, learned more, little change in certain areas of inquiry as seen in pre/post definition and final lesson plan. Content: Properties of matter and changes in matter. Krall et al. (2009): 43 teachers grade 4-8 from Appalacia (KY). 30-40 hour online short course. Significant gains for 81.4% of teachers in six of 9 science concept topics (temperature/heat). Rated kits and investigations most high, then CD-ROM at 68%. Some teachers formed cohorts if geographically close to each other to work through and discuss experiments. Email support ranked lowest, compared to teacher journals. Owsten et al. (2006): 33 science teachers. Online requested reflective posting to journal articles (not sharing/discussing student work like Berger). Difficult to share online with strangers, not rich/immediate feedback to their postings online
  • Harlen and Doubler (2004): Online and f2f course in science content and inquiry (15 and 18 N respectively). Inquiry and investigations most valuable, online spent more time, higher confidence, learned more, little change in certain areas of inquiry as seen in pre/post definition and final lesson plan. Content: Properties of matter and changes in matter. Krall et al. (2009): 43 teachers grade 4-8 from Appalacia (KY). 30-40 hour online short course. Significant gains for 81.4% of teachers in six of 9 science concept topics (temperature/heat). Rated kits and investigations most high, then CD-ROM at 68%. Some teachers formed cohorts if geographically close to each other to work through and discuss experiments. Email support ranked lowest, compared to teacher journals.
  • 1 st : Proportion of Variance (R2) in dependent variables (achievement, learner content preference) explained by independent variables (age/years experience/learning style). 2 nd : Additional regressions look at individual relationships comparing dependent variables and regression coefficient to independent variables..see where relationships exist. IF no prior ideas about which variables will create best prediction equation and reasonably small set of predictors, simultaneous multiple regression best method to use (Leech et al. 2008).
  • Explore relationships btw learning achievement as measured by pre/post assessment (dependent) across multiple science content areas and age/years experience (independent). Variables should be mostly interval/scale data, which applies here. If multicollinearity exists between variables (age/yrs teaching experience), examined for “TOLERANCE’ with each other to help avoid misleading results if predictor variables overlap. One solution if tolerance low and collinearity is high: Combine them into one block if they are indicators of the same variable.
  • Pooled Error Estimate, ANOVA more conservative test compared to running many side-by-side two variable t-tests (learner preference to one of each of the 5 types of content interaction individually). This ensures error is not underestimated. TUKEY: which means are significantly different then one another. Compares means of every treatment to means of every other treatment, simultaneously to all pairwise comparisons. Run post hoc comparison AFTER significance found ON A SUBSET OF THE DATA LOOKING TO GLEAN ADDITIONAL INFO (PATTERNS), to help eliminate significance due to chance (largest differences btw means), use post hoc PAIRWISE comparisons (comparing 2 specific means at a time), REQUIRES larger difference between means to call differences significant…AS OPPOSED TO critical value difference btw means for significance). IF DIFFERENCE OBTAINED IS GREATER OR EQUAL TO CRITICAL DIFFERENCE, IT IS SIGNIFICANT.
  • Preliminary Exam

    1. 1. Examining Learning-Content Interaction Importance and Efficacy in Online, On-Demand Electronic Professional Development in Science for Elementary Educators in Grades 3-6 Prospectus Exam and Proposal November 2009 Al Byers
    2. 2. <ul><li>Provide brief review of pre-prospectus document and tentative plans for dissertation study </li></ul><ul><li>Literature Review : Elementary teacher science content knowledge, lack of PD in support of same and potential of online PD to address issue </li></ul><ul><li>Research Purpose and Question: Along with Supporting Theories--Anderson Equivalence of Interaction Theory, 2003 </li></ul><ul><li>Research Hypotheses : Five Hypotheses </li></ul><ul><li>Methodology, Variables and Instruments (and literature in support of same) </li></ul><ul><li>Timeline (Prospectus Fall 09, Defend Spring/Summer 010) </li></ul>Focus of Presentation
    3. 3. Literature Review
    4. 4. <ul><li>US students scores on national and international science assessments stagnant (NAEP 2000, 2006; TIMSS 2007; PISA 2006) </li></ul><ul><li>Elementary and Middle level Teachers’ Content Knowledge Lacking and PD Inadequate to address needs (Banilower et al. 2007; Dede et al. 2006; Elmore 2004; Garet et al. 2001; Loucks-Horsley 1999; US Dept. of Ed 2009; Yoon et al. 2008) </li></ul><ul><li>Online Teacher PD: Potential Compliment to Face-to-Face PD to address scale (Dede et al. 2006, 2009; National Research Council 2007) </li></ul>State of Affairs in Science Education in United States: Need for Improvement in Science Instruction More Info
    5. 5. <ul><li>Rise in student scores nationally and internationally slow. </li></ul><ul><ul><li>2000 NAEP : Only 29% of 4 th and 8 th grade students at proficient level. Flat across all grades in science last 30 years </li></ul></ul><ul><ul><li>2007 TIMSS : Dozens of nations in grades 4 and 8 tested. US shows little growth in science since 1995. Ranked behind 11 other nations for 8 th grade science. At grade 4, only 4 nations statistically higher. By 12 th grade, we are last among 20 competing nations. </li></ul></ul><ul><ul><li>2006 PISA in Science : For 15 year olds, US ranked below top 20 countries tested (29 th out of 53 nations and scored below the overall average score for PISA) </li></ul></ul>US Students Scores in Science Stagnant: Drive Focus on Teachers
    6. 6. Elementary and Middle Level Teachers of Science Elementary School Teachers 80% 74% Vast majority of K-8 teachers have general education degree, not in science or science education Horizons Research (2001) At middle school level (grades 5-8), large percentages of teachers “within-field” teaching “out-of-field” Ingersoll (1999) There are approximately 1.7 million elementary teachers in United States NCES (2000) Middle School Teachers 20% 40% 60% 80%
    7. 7. Elementary and Middle Level Teachers of Science Middle School Teachers Elementary School Teachers 71% 67% Vast majority of K-8 teachers expressed need to deepen their own science content knowledge (67-71%). Only 18-29% of K-4 teachers felt well prepared to teach science. Horizons Research (2001); NSDC (2008) Content-related PD top priority requested by teachers in 03-04 NCES SASS survey 20% 40% 60% 80%
    8. 8. Overview of Curriculum, Instruction and Assessment on Science in US Study National Reform Findings Elmore (2004) School research in classrooms across US over years Elementary teachers have little knowledge of various curriculum & assessment for science, nor support to implement effectively within classroom CCSSO (2007) Analysis of NCES 2004 Schools and Staffing Survey 50% Elementary teachers in US in self-contained classrooms responsible all subjects, little formal preparation in science. Only spend 2-3 hrs/week on science grades 1-6 (down from 3.5 hrs/week on 1994 SASS) Griffin (2008) State-wide N=164, volunteer survey Due to NCLB, survey shows 60% report decreased time on science spending as little as 1.5 hrs/wk Ma (1999) Comparison of US vs. China methods and classrooms Elementary math teachers less formal schooling then US, but deeper knowledge of content and PCK, team lesson analysis difference, more planning time
    9. 9. <ul><ul><li>is fragmented, lacks coherence, evaluation of effectiveness; insufficient follow-up, time, and is not part of school-wide reform effort for sustainability. </li></ul></ul><ul><ul><li>in large part comprises online short courses using very little hands-on inquiry, simulations, or learning objects. Primarily asynchronous discussion. </li></ul></ul><ul><ul><li>is of an insufficient duration and frequency to affect lasting change in teachers’ practice or increases in student learning, and not within theoretical framework </li></ul></ul>Professional Development at a Glance Dede et al. (2006); Elmore (2004); Loucks-Horsley (1999); US Dept. of Ed (2009) Sloan Consortium (2008); Asbell-Clark & Rowe (2007) Banilower et al. (2007); Dede et al. (2009); Garet et al. (2001); Yoon et al. (2008)
    10. 10. <ul><ul><li>US Partnerships in Mathematics and Science </li></ul></ul><ul><ul><ul><li>In 05-06 invest $181 million dollars </li></ul></ul></ul><ul><ul><ul><li>Funded 501 programs </li></ul></ul></ul><ul><ul><ul><li>Average expenditure per program: $337,015 </li></ul></ul></ul><ul><ul><ul><li>Average teachers reached: 113 </li></ul></ul></ul><ul><ul><ul><li>Primary model: Summer Institute with follow-up site visits </li></ul></ul></ul><ul><ul><ul><li>Total teachers Reached: 56,000 </li></ul></ul></ul><ul><ul><ul><li>Total teachers of science in US: 3 Million </li></ul></ul></ul><ul><ul><li>If funding levels do not change, take over 50 years to impact all our nations teachers using this model </li></ul></ul><ul><ul><li>Online PD may be way to address scale on level that is sustainable </li></ul></ul>Challenges of Face-to-Face Professional Development US Department of Education (2006) Return
    11. 11. Research Purpose/Question and Supporting Theories 11
    12. 12. Research Purpose and Question <ul><li>The intent of this quantitative study is to determine which features of on-demand, self-directed online professional development are of greatest import, satisfaction, and learning value from a sample of upper elementary science teachers (grades 3-6). </li></ul><ul><li>Anderson’s 2003 Equivalence of Interaction Theorem will be utilized, focusing on learner-content interaction versus learner-learner, or learner-instructor interaction </li></ul>12
    13. 13. Research Purpose and Question <ul><li>Interactive features in self-paced on-demand web modules will be examined across science content areas : </li></ul><ul><ul><li>Interactive Reference Content </li></ul></ul><ul><ul><li>Embedded Hands-on Activities </li></ul></ul><ul><ul><li>Personal Feedback Questions </li></ul></ul><ul><ul><li>Simulations </li></ul></ul><ul><ul><li>Pedagogical Implications </li></ul></ul><ul><li>Learning Content Preferences will be measured via an online survey and regressed against learner age and years teaching experience . </li></ul><ul><li>Learning Achievement will be regressed against age and years teaching experience using NSTA’s Pre/Post Assessment tool. </li></ul><ul><li>Learning Styles measured via Kolb (2005) Learning Style Inventory 3.1 will be compared against learning preferences and perception of learning impact for different learner-content interaction types via multiple one-way analysis of variance . </li></ul>13
    14. 14. Research Purpose and Question <ul><li>It is hoped research findings will: </li></ul><ul><li>Inform Instructional Designers creating online PD as to which components of online content may be most engaging and maximize learning for elementary teachers </li></ul><ul><li>Inform Education Administrators charged with selecting PD for their teachers based on their audience make-up </li></ul><ul><li>Inform emerging theory related to online learner-content interaction: Anderson’s (2003) theory of interaction equivalence </li></ul>14
    15. 15. Anderson Equivalence of Interaction <ul><li>“ Deep and meaningful formal learning is supported as long as one of the three forms of interaction ( learner–instructor; learner-learner; learner-content ) is at a high level. The other two may be offered at minimal levels, or even eliminated, without degrading the educational experience. High levels of more than one of these three modes will likely provide a more satisfying educational experience, though these experiences may not be as cost or time effective as less interactive learning sequences” (2003, p. 4). </li></ul>
    16. 16. Learner-Content Interaction Focus (Anderson, 2003) <ul><li>Still challenge to define when interaction has educational value </li></ul><ul><li>Broad combination of delivery modes and pacing should be available (del Valle et al. 2009; Krall et al. 2009; Rhodes 2009; Russell; 2009) </li></ul><ul><li>Increase networking & computer power warrant exploration of student-content interactions </li></ul><ul><li>Independent study materials (e.g., simulations, quizzes, learning objects) may enhance learning and minimize instructor interaction (Asbell-Clarke et al. 2007; Sherman et al. 2008; Walker et al. 2008) </li></ul>Self-Directed Studies
    17. 17. Research in K-8 Online PD (Self-Directed Online Learning Studies) Study PD Model Audience/Content Research Findings del Valle et al. (2009) Self-paced, 12 week module, instructor help K-12 inservice teachers--24 from elementary Mastery-sig. time over longer period, Task-focused-less time in shorter per. Procrastinator-little time, long pd Krall et al. (2009) Self-paced, on-demand, hands-on kits, mentor 43 Elem. & Middle Science and Inquiry, grades 4-8 Significant gains in content & conceptual knowledge. Email Mentor rated lowest across all interaction Lapointe et al. (2008) Evaluate import of online community 74 adult grad students out of 412, 30 disciplines Perception survey and quantitative data reveal mixed results. Not all favor peer-peer interaction (split) Rhodes (2009) Self-paced courses part of certificate model 10 adults in undergrad ed tech PD courses Learners interacted most with content and instructor and ranked ahead of learner-learner interaction Russell et al. (2008) Compare 8 wk online PD, varied support 145 Middle level math teachers (grades 5-8) Sig. gains in pedagogy and content knowledge across all delivery/ support modes. NSD between mode Walker et al. (2008) Online modules, email support In & Pre-service, K-8 grades (N=32) Survey: high ease of use, and enhanced instruction (self-reported)
    18. 18. Research in Online PD in Science Education Return Study PD Program Model Target Audience/ Content Area Research Findings Asbell-Clarke (2007) 40 moderated online courses and 35 instructors, across 6 institutions. Middle and high science (Over 200 students) Large Instructor controlled asynchronous discussion. Little hands-on or projects Harlen et al. (2004) Short course w/ hands on inquiry (compare w/ f2f) Elementary and Middle Science (N = 15 and 18 respectively) Online group significant learning gains and time spent. Inquiry more difficult Sherman et al. (2008) Self-paced, mentor, learning objects Middle school science and inquiry (N = 43) Significant gains in content knowledge and self-efficacy
    19. 19. Anderson’s Equivalence of Interaction
    20. 20. Anderson’s Equivalence of Interaction Many focus on learner-learner or learner-instructor interaction. This study will focus on importance and learning efficacy of learner-content interaction.
    21. 21. Learner-Content Interaction Types <ul><li>Interactive Reference: Content narrative, images, animations, audio and glossary (Schaller et. al 2002, 2007) </li></ul><ul><li>Hands-On Opportunities: Activities to learn content via tactile inquiries (Krall et al. 2009; Harlen et al. 2004) </li></ul><ul><li>Pedagogical Implications: Application of content in classroom contexts by grade band (Asbell-Clarke 2007; Berger et al. 2008; Harlen et al. 2004;Owston et al. 2006; Russell et al. 2008 ) </li></ul><ul><li>Simulations: Control of relational variables, phenomenon (Schaller et al. 2002, 2007; Sherman et al. 2008) </li></ul><ul><li>Personal Feedback: Provided for individual (del Valle et al. 2009; Whitaker et al. 2007; Hoskins et al. 2005) </li></ul>Interaction Research
    22. 22. Research in Online PD in Science Ed (Pedagogical Content Knowledge Addressed Online) Study PD Program Model Target Audience/ Content Area Research Findings Asbell-Clarke (2007) 40 moderated online courses, review across courses 250 K-12 science educators and 35 instructors completed pre/post questionnaires Instructor lead asynchronous discussion. Little hands-on or sims. Students felt supported and large discourse regarding pedagogy and self-reflection. Berger et al. (2008) Monthly f2f with online blend in-between (9 months) 16 High School Physics Teachers (in Israel) Strong online participation linked to student work. Build off teacher queries/ideas Owston et al. (2006) 4 f2f workshops between 8 weeks online. 25 weeks. Two cohorts Middle Science & Math. 65 science teachers (in Canada) Significant gains in teacher perception of inquiry. Weak online participation. Difficult to take release time provided Russell et al. (2009) 8 wk online PD include pedagogical activities such as preparing lessons, online discussions 145 Middle level math teachers (grades 5-8) Using pre/post pedagogical beliefs and practices survey found all groups show significant gain in self-reported inquiry-based practices
    23. 23. Research in Online PD in Science Ed (Simulations, Hands-On Inquiry, Interactive Reference) Return Examples Study PD Model Target Audience/ Content Area Research Findings Harlen et al. (2004) Short course w/ hands-on inquiry (compare w/ f2f) Elem. & Middle Science (15 and 18 in each group) Online group significant learning gains and time spent. Inquiry more difficult Krall et al. (2009) Self-paced, hands-on kits, mentor Elem. & Middle Science & Inquiry Significant gains in content knowledge. Low mentor rating. Sherman (2008) Self-paced, email, learning object with simulations Middle school science/inquiry Significant gains in content knowledge & teacher self-efficacy Schaller et al. (2002) Museum content-web sites/web logs 2 groups (adults/ children) N=549 Adults preferred Interact. Ref. & Simulations. Kids preferred role playing and games Schaller et al. (2007) Museum web sites (content-type) 7,800 exit surveys from 11 museums Learning style affects adult pref. Social-Role Play, Intellectual--Interactive Ref.
    24. 24. Learner-Content Interaction Types Interactive Reference: Content narrative, images, slide shows, animations, audio and glossary classified as interactive reference permitting learner to engage in content via playback of animations, movies, check-your thinking mouse-overs, etc. (Hoskins et al. 2005; Schaller et al. 2002, 2007)
    25. 25. Interactive Reference
    26. 26. Interactive Reference
    27. 27. Interactive Reference
    28. 28. Learner-Content Interaction Types Hands-On Opportunities: Activities to learn content via tactile mode via simplistic yet elegant inquiry using items readily available within home. Not a full-blown student lesson plan. (Asbell-Clarke et al. 2007; Harlen et al. 2004; Krall et al. 2009; NRC 1996)
    29. 29. Hands-On Activities
    30. 30. Learner-Content Interaction Types Pedagogical Implications: Translation of content for classroom contexts by grade band (e.g., strategies for teaching difficult concepts, what cognitively appropriate by grade band, K-2, 3-5, 6-8, 9-12) and as aligned to both the National Science Education Standards and AAAS Benchmarks for Science Literacy (Berger et al. 2008; Asbell-Clarke et al. 2007; Russel et al. 2009; Owston et al. 2006)
    31. 31. Pedagogical Implications
    32. 32. Pedagogical Implications
    33. 33. Learner-Content Interaction Types Simulations: Control of relational variables to observe differences in science content phenomenon under examination (e.g., height ball dropped, angle down hill, type of surface ball rolling across (Anderson 2003; Asbell-Clarke et al. 2007; Sherman et al. 2008; Schaller et al. 2002, 2007; Bayraktar, 2001; Kulik, 1991; J. Lee, 1999; Vogel, et al., 2006)
    34. 34. Simulations Air Gravity Cart Track Plate Tectonics Seismic Waves Make a Reef Reflecting Light Curved Mirrors
    35. 35. Learner-Content Interaction Types Personal Feedback: Feedback provided for individual learners based on selections they make as answering varied question types that are embedded throughout content and as quizzes at the end of each section (e.g., multiple choice answers, drag-n-drop hotspots, sequencing questions, etc.) (Hoskins et al. 2005; Lapointe et al. 2008; Rhodes et al. 2009)
    36. 36. Personal Feedback
    37. 37. (Appendix D)
    38. 38. Ex: Frequency of Interaction one web module Return Appendix D Survey
    39. 39. Research Hypotheses <ul><li>H1: Age will be correlated with the type of preferred interaction desired in self-directed web-based modules (del Valle et al. 2009; Farahani, 2003; Hoskins et al. 2005; Jiang et al. 2006; Kayes 2005; Schaller et al. 2007) </li></ul><ul><li>H2: Years teaching experience will be correlated with the type of preferred interaction desired in on-demand, self-directed web-based modules (del Valle et al. 2009; Kayes 2005) </li></ul>
    40. 40. Research Hypotheses <ul><li>H3: Age will be correlated with the achievement as measured via a pre/post assessment for those that have completed and passed an online web module (del Valle et al. 2009; Hoskins et al. 2005; Kayes 2005). </li></ul><ul><li>H4: Years teaching experience will be correlated with achievement as measured via a pre/post assessment for those that have completed and passed an online web module (del Valle et al. 2009; Kayes 2005; Russell et al. 2009) </li></ul>
    41. 41. Research Hypotheses <ul><li>H5: Adult learners prefer an online interaction type matching their learning style when accessing self-directed online PD focused on learner-content interaction (Lapointe et al. 2008; Rhode 2009; Schaller et al. 2002; 2007; Su et al. 2005; Farahani 2003; Harlen et al. 2004; Kolb et al. 2005; Krall et al. 2009) </li></ul><ul><li>Teachers selecting Interactive Reference most favorable will be identified with “Assimilating” learning style </li></ul><ul><li>Teachers selecting Hands-On activities most favorable will be identified with “Accommodating” learning style </li></ul><ul><li>Teachers selecting Pedagogical Implications most favorable will be identified with “Converging” learning style </li></ul><ul><li>Teachers selecting Personal Feedback most favorable will be indentified with “Diverging” learning style </li></ul><ul><li>Teachers selecting Simulations most favorable will be identified with “Converging” learning style </li></ul>Variables Research
    42. 42. Variables: Age, Work Experience, Achievement, Perception Study Study Design Aud./Content Research Findings Del Valle et al. 2009 Content usage in on-demand 12 wk course, cluster analysis determined 3 distinct groups of learners online 59 teachers, 24 elementary. On-demand course on inquiry & tech integration with email mentoring. Three Groups: Mastery oriented, Task Focused, Procrastinators. Mastery most sessions & time. Task Focused shorter time, more logins then procrastinators-least time, fewest logins. Work Experience: Mastery group significant more yrs experience vs. task focused group. Minimalist group: Prefer cohort group envir. Age: NSD among 3 clusters. Self-Reported Learning: All report learned, NSD found between cluster groups. Hoskins et al. 2005 Tool/content usage-online quizzes, dis. boards, etc. Multiple linear regressions and discriminate function analysis to predict use. 110 ungrads, 12 wk blended course in biological psychology. Analysis of Covariance determine web use impact on achievement Age: Older students (>21 yrs) put forth more effort to process content at deeper level for more intrinsic reasons. As age increased, number of logins and time online increased, and use of discussion boards. Study Approach: As lower achievement oriented learners completed more quizzes they learned more, higher achievement oriented users access more content/tools. Academic Achievement: Increased use of discussion board predicted increase achiev.
    43. 43. Hoskins et al. 2005 <ul><li>Close study with a call to examine components in online learning environments in more detail and to explore the use of content and delivery styles in an effort to maximize student engagement and learning. Given the small sample of older learners, the authors conclude with a call for more research to confirm or refute the findings with a larger population of mature learners </li></ul>
    44. 44. Variables: Learner-Content Type, Learner Preference by Age Study Study Design Aud./Content Research Findings Schaller et al. 2002 Online exit surveys across 5 museum web sites for 549 users Interaction types: Creative play, guided tour, interactive reference, puzzle/mystery, role play, simulation Learning Preference: Sig. Diff. found among types of web-based learning between kids and adults. Adults: favored interactive reference and simulations Kids: Creative Play or Role Play Novice Learners: Regardless of age preferred Guided Learning web modules. Schaller et al. 2007 Two separate online exit surveys across 11 museum web sites for 5606 users, 2298 adults. Use Kolb LSI 3.1 for preference Middle & High School kids and Adults. Content Interaction Types: Interactive Reference, Discussion, Design, Simulation, Role Play, Puzzle-Mystery Learning Preference: Sig. Diff. Adults: Learning style influence preferences for learning activities. As get older move from Accommodating style to more Assimilating and Converging learning styles Age: Adults prefer Int. Reference and Puzzle, Kids--Role-Play, & Design. Gender: Female adults-more social then male adults. Kids-NSD
    45. 45. Variables: Learner preference, Achievement, Age, Work Exp. Study Study Design Aud./Content Research Findings Kayes 2005 Internal validity and reliability of Kolb 3.1 221 undergrad and grad business students completed Kolb 3.1 Found significant differences in learning preferences between undergrads and grads. Researchers attributed to age or work experience. Russell et al. (2008) Compare 8 wk online PD, varied support. 70% female. 145 Middle level math teachers (grades 5-8). 48%< 40 yrs old. No further breakdown Sig. gains in pedagogy and content knowledge across all delivery modes. NSD between modes. NSD between support groups on demographic variables—teachers self-selected mode. Brittan et al. (2008) Learning styles on academic course achievement & course selection 108 undergrad students at HBCU (91% female). Psychological Assessment course (online or f2f compared). Self select enrollment Surveyed students who volunteered to take Kolb after completing f2f exam. Using Chi-Square found NSD between learning style and course delivery preference. NSD also found between course grade (achievement) and course delivery format (2X4 ANOVA). Researchers call for re-evaluation of learning styles given interaction available in online learning environments
    46. 46. Methodology, Variables and Instruments
    47. 47. Methodology <ul><li>Multi-Statistical Method study </li></ul><ul><li>Simultaneous multiple regressions and Multiple One-Way Analysis of Variance </li></ul><ul><ul><li>Dependent Variables: </li></ul></ul><ul><ul><ul><li>Learning Achievement </li></ul></ul></ul><ul><ul><ul><li>Teacher preference of, perception for and learning effectiveness of the five learning-content interaction types </li></ul></ul></ul><ul><ul><li>Independent Variables: </li></ul></ul><ul><ul><ul><li>Learner Age </li></ul></ul></ul><ul><ul><ul><li>Years Teaching Experience </li></ul></ul></ul><ul><ul><ul><li>Learning Style </li></ul></ul></ul>
    48. 48. Methodology <ul><li>H1 and H2: </li></ul><ul><li>Simultaneous Multiple Regression 1 </li></ul><ul><ul><li>Dependent Variables (interval data): </li></ul></ul><ul><ul><ul><li>Teacher preference of, perception for and learning effectiveness of the five learning-content interaction types ( measured via learner preference survey ) </li></ul></ul></ul><ul><ul><li>Independent Variables (continuous ratio data): </li></ul></ul><ul><ul><ul><li>Learner Age </li></ul></ul></ul><ul><ul><ul><li>Years Teaching Experience </li></ul></ul></ul>
    49. 49. Methodology <ul><li>H3 and H4: </li></ul><ul><li>Simultaneous Multiple Regression 2 </li></ul><ul><ul><li>Dependent Variables (interval data): </li></ul></ul><ul><ul><ul><li>Learning Achievement ( measured via NSTA post assessment instrument ) </li></ul></ul></ul><ul><ul><li>Independent Variables (continuous ratio data): </li></ul></ul><ul><ul><ul><li>Learner Age </li></ul></ul></ul><ul><ul><ul><li>Years Teaching Experience </li></ul></ul></ul><ul><ul><ul><li>Pre-Assessment (covariant, items same as post assessment) </li></ul></ul></ul>
    50. 50. Methodology <ul><li>H5: </li></ul><ul><li>Multiple One-Way Analysis of Variance </li></ul><ul><ul><li>Dependent Variables: (interval data) </li></ul></ul><ul><ul><ul><li>Teacher preference of, perception for, and learning effectiveness of five content interaction types ( Likert scale survey ) </li></ul></ul></ul><ul><ul><li>Independent Variable: (categorical determined via interval data): </li></ul></ul><ul><ul><ul><li>Learning Style Preference ( via Kolb LSI 3.1 ) </li></ul></ul></ul><ul><ul><ul><ul><li>Accommodating </li></ul></ul></ul></ul><ul><li>Diverging </li></ul><ul><ul><ul><ul><li>Converging </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Assimilating </li></ul></ul></ul></ul>
    51. 51. Methodology <ul><li>H5 Analysis Steps: </li></ul><ul><li>Classify learners into individual groups based on their learning style preference (diverging, assimilating, converging, accommodating) </li></ul><ul><li>Run multiple one-way ANOVAs for each preference group to examine which content interaction types most preferred based off teacher preference/perception of constructs: </li></ul><ul><ul><ul><ul><li>Content Engagement Level </li></ul></ul></ul></ul><ul><li>Facilitate Learning Science </li></ul><ul><ul><ul><ul><li>Facilitate Content Retention </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Ability to Teach Content </li></ul></ul></ul></ul><ul><ul><ul><ul><li>Content Preference Type </li></ul></ul></ul></ul>
    52. 52. Instruments: Kolb Learning Style Inventory 3.1 (2005) <ul><ul><li>Developed in 1969, revised in 1985, 1999 and 2005 </li></ul></ul><ul><ul><li>Adheres to standards for educational testing by American Educational Research Association </li></ul></ul><ul><ul><li>12 item survey with 4 “forced choice” questions </li></ul></ul><ul><ul><li>Learners placed in one of 4 learning styles </li></ul></ul><ul><ul><li>Used in over 650 studies for research across multiple groups, including education, normative testing group –over 6977 users </li></ul></ul><ul><ul><li>Average internal reliability (test-retest) alpha of .81 (range .73 to .99) </li></ul></ul><ul><ul><li>Internal Construct Validity for learning preference categories (CE, AE, RO, AC). Range .77 to .82 (Kayes 2005) </li></ul></ul>Kolb Studies
    53. 53. Selected Kolb Learning Preference Studies Study Study Design Aud./Content Research Findings Felder et al. 2005 Varied teaching strategies needed to accommodate different learning preferences. Literature review-Kolb Engineering Students. Three categories diversity have important implications for teaching and learning. Literature Review: Differences in students’ learning styles (characteristic ways of taking in and processing information-Kolb 3.1), Approaches to learning (surface, deep, and strategic) Intellectual development levels (attitudes about the nature of knowledge and how acquired and evaluated). Brittan et al. (2008) Role learning styles on academic course achievement and preferences for course selection 108 undergrad students at HBCU (91% female). Psychological Assessment course (online or f2f compared). Self select enrollment mode. Surveyed students who volunteered to take Kolb after completing f2f exam. Using Chi-Square found NSD between learning style and course delivery preference. NSD found between course grade (achievement) and course delivery format (2X4 ANOVA). Researchers call for re-evaluation of learning styles given interaction available in online learning environments
    54. 54. Selected Kolb Learning Preference Studies Return Study Study Design Aud./Content Research Findings Schaller et al. 2007 Two separate online exit surveys across 11 museum web sites for 5606 users, 2298 adults. Use Kolb LSI 3.1 for preference Middle & High School kids and Adults. Content Interaction Types: Interactive Reference, Discussion, Design, Simulation, Role Play, Puzzle-Mystery Learning Preference: Sig. Diff. Adults: Learning style influence preferences for learning activities. As get older move from Accommodating style to more Assimilating and Converging learning styles Age: Adults prefer Int. Reference and Puzzle, Kids--Role-Play, & Design. Gender: Female adults-more social then male adults. Kids-NSD Kayes 2005 Internal validity and reliability of Kolb 3.1 221 undergrad and grad business students completed Kolb 3.1 Found significant differences in learning preferences between undergrads and grads. Researchers attributed to age or work experience.
    55. 55. Kolb Learning Style Inventory 3.1
    56. 56. Instruments: NSTA Content Knowledge Assessment <ul><li>Stage 1: Item Development (Appendix B) </li></ul><ul><li>Step 1-Identify and train item developers </li></ul><ul><li>Step 2-Item developers generate items based on web module evidences of understanding </li></ul><ul><li>Step 3-Items submitted to subject matter experts </li></ul><ul><li>Step 4-Items edited by assessment expert </li></ul><ul><li>Stage 2: Pilot Testing </li></ul><ul><li>Step 5-Prepare items for online pilot testing and recruit pilot testers </li></ul><ul><li>Step 6-Collect pilot data and analyze pilot results (point biserial item analysis) </li></ul><ul><li>Stage 3-Final Item Selection </li></ul><ul><li>Step 7-Item reviewers evaluate pilot data (two reviewers per set) </li></ul><ul><li>Step 8-Item review team evaluates items for bias & content alignment with stated evidences of understanding </li></ul><ul><li>Step 9-Select final items based on item reviewer recommendations </li></ul><ul><li>Step 10-Test-level analysis on selected items conducted (Chron. Alpha) </li></ul><ul><li>Stage 4-Final Item Preparation </li></ul><ul><li>Step 11-Clean up graphics and edit copy </li></ul>
    57. 57. NSTA Content Knowledge Assessment: Sample Chronbach Alpha Internal Consistency Test No. of Items No. of Cases Mean Internal Consistency* Earth History 20 111 62.3 .704 Food Science Safety 22 102 61.7 .787 Magnetic and Electric Forces 22 114 56.1 .821 Nature of Light 20 105 55.6 .737 Resources and Human Impact 16 100 79.0 .656 Atomic Structure 16 102 65.9 .882 Cell Structure and Function 23 261 13.2 .636 Chemical Reactions 23 101 60.5 .877 Elements, Atoms, & Molecules 28 103 83.3 .812 Nutrition 20 97 67.5 .609 Cell Division & Differentiation 22 97 69.1 .752 Cells & Chemical Reactions 24 94 59.4 .821
    58. 58. Instruments: Learner Demographic/Preference Survey <ul><ul><li>Online Survey Example (Appendix E) </li></ul></ul><ul><ul><ul><li>Age </li></ul></ul></ul><ul><ul><ul><li>Years Teaching Experience </li></ul></ul></ul><ul><ul><ul><li>Subjects Certified to Teach </li></ul></ul></ul><ul><ul><ul><li>Learner content-type preferences for and perception of: </li></ul></ul></ul><ul><ul><ul><ul><ul><li>Content Preference by Type (5 types) </li></ul></ul></ul></ul></ul><ul><ul><ul><ul><ul><li>Content Engagement Level by Type (5 types) </li></ul></ul></ul></ul></ul><ul><ul><ul><ul><ul><li>Facilitation of Learning Science Content </li></ul></ul></ul></ul></ul><ul><ul><ul><ul><ul><li>Facilitation of Content Retention </li></ul></ul></ul></ul></ul><ul><ul><ul><ul><ul><li>Facilitation to Teach Content to Students </li></ul></ul></ul></ul></ul><ul><ul><ul><ul><ul><li>NOTE: Capture age, yrs experience, and grades taught as fill in blank in survey (or multiple check boxes), not categorical range, permits finer distinction between independent variables, grouping may still occur </li></ul></ul></ul></ul></ul>Content Types
    59. 59. Population for Analysis <ul><ul><li>Self-selected participants volunteering for study </li></ul></ul><ul><ul><li>Invited via Email, receive $39 free web module if complete survey, only draw from grades 3-6 that have completed and passed web module. </li></ul></ul>Web Module Science Content Area Number Completed Pretest online Number Passed Web Module Final Assessment Number Completed Posttest online Force and Motion 1144 533 255 Energy 553 335 150 Ocean’s Effect on Weather and Climate 305 141 56 Rock Cycle 202 72 60 Earth, Sun & Moon 294 145 59 Cell Structure and Function 226 183 43 Totals 2,724 1,409 623
    60. 60. Timeline <ul><ul><li>November 2009 </li></ul></ul><ul><ul><ul><li>Pass Prospectus Exam </li></ul></ul></ul><ul><ul><ul><li>Secure IRB approval </li></ul></ul></ul><ul><ul><ul><li>Review database of potential participants for study </li></ul></ul></ul><ul><ul><ul><li>December 2009 </li></ul></ul></ul><ul><ul><ul><li>Invite teachers to participate in study </li></ul></ul></ul><ul><ul><ul><li>Finalize list of those that agree to participate </li></ul></ul></ul><ul><ul><ul><li>January 2010 </li></ul></ul></ul><ul><ul><ul><li>Forward URL to Kolb LSI and Preference Survey </li></ul></ul></ul><ul><ul><ul><li>Dillman method to increase response rate </li></ul></ul></ul><ul><ul><ul><li>February 2010 – April 2010 </li></ul></ul></ul><ul><ul><ul><li>Analyze Data </li></ul></ul></ul><ul><ul><ul><li>Generate tables/figures, Write Conclusions </li></ul></ul></ul><ul><ul><ul><li>May 2010 – July 2010 </li></ul></ul></ul><ul><ul><ul><li>Defend and Complete Dissertation </li></ul></ul></ul>

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