Saad Chahine Thesis Presentation Final

568 views
538 views

Published on

This is my PHD Defense presentation. Successfully defended July 28th, 2011

Published in: Technology, Education
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
568
On SlideShare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
0
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide
  • Quick 1) Thank committee members for their support and guidance
  • Quick Great deal of pressures on school and educators to use data from large scale assessment & We know very little about Potentially there is a compromise to our new notions of validity because we dot understanding how educators interpret and use score reports
  • QuickThis literature review started with the ideas of validity and the lack of investigation in educators interpretation and proposed use of score reports. I then examined what reports ought to look like to facilitate understanding and relate it to the initial intended proposes. Once you examine those, it is then left to the educator to interpret the score reports. The ways in which an educator proposes to use test score reports depends on their Data Habit of Mind.
  • Medium Talk about Dat Keating & Robert SternbergI conceptualized data habit of mind in this thesis as a combination of having a general fluency with data and information, that what I call statistical literacy and the ways in which an educator would read interpret and potentially use score report. Initially I wanted to be able to plot educators for example you may have an educator who is very proficient in stats like a mathematics teacher but does not use the results from students assessment. However Data habit of mind does not exist in a vacuum and it is a metaphor that was coined by Keating and Sternberg to help explain the habits we have in every day life. The problem is there are contexts in which these habits exist.
  • Quick Data habit of mind does not exist in a vacuum,In this model I belive that datahabit of mind would be directly related to the ways in which educator in reali life use the information which will in turn improve school and student achievement This is relationship potenttially mediated by culture of of the school which is often influeced by political pressures and the different types of reporting that may happen
  • Quick About statistical literacy Score Report intretrpationFinding a relationship between the two Trying to relate the relatiohship to some background variables
  • Quick Requretmrnt not sampling or valuenter Educators
  • Quick & refer to hand outs for reports
  • Very Quick
  • Quick
  • Longer & Explain coding & Thinking levels based on the SOLO taxonomy Horizontal are the different concepts f statistical literacy, a person myabe high on describing and low when it comes to representing for example
  • Quick Each response was coded to be either Idiosyncratic, Transitional, Quantitative, Analytical Describing: Educators had an easy time Organizing and Reducing: A little more difficult because of the word typical to describe central tendency Representing: Educators always tried to push the bar graphAnalyzing and Interpreting: Was mixed – some educators had difficulty while others found it easier
  • Longer & Explain Coding Horizontal are the different concepts of score report interpretation literacy, a person maybe high on describing and low when it comes to questioning for example
  • Longer Talks about both reports at the same time Describing: Educators were coded very high for this in both reports Summarizing: Educators were able to summarize the reports very well Questioning: Great deal of variability observedProposing an application: Great deal of variability observed
  • Longer Refer to hand outsLower Statistical Literacy and Lower Questioning & Proposed Application: E 11 -Higher Statistical Literacy and Lower Questioning & Proposed Application: E4, E5, E7, E13
  • Longer Educators with overall statistical literacy scores below 2 were placed in the Idiosyncratic category, between 2 and 3 were placed in the Transitional category, between 3 and 3.5 were placed in the Quantitative category, and above 3.5 were placed in the Analytical category.
  • Longer Questioning for coopers – say your only going to show one example, though the thesis describes this in much more detail -Lower Statistical Literacy and Lower Questioning & Proposed Application: E 11 -Higher Statistical Literacy and Lower Questioning & Proposed Application: E4, E5, E7, E13 -All other educators coding of questioning and proposed application differed with the different reports -25% of sample were not coded differently based on the reports.
  • Longer Educators shifted back and forth while some remained the same Of the ones who remained the same quadrant who remained the same in both proposed application and Questions between the two This tells us that only 5 educators have the same codes when it came to questioning and proposed application irrelevant f the report, While other educators would change there level of questioning and proposed application based on the report-Lower Statistical Literacy and Lower Questioning & Proposed Application: E 11 -Higher Statistical Literacy and Lower Questioning & Proposed Application: E4, E5, E7, E13 -All other educators coding of questioning and proposed application differed with the different reports -25% of sample were not coded differently based on the reports.
  • Though one might expect to see a relationship I did not find meaningful relationshipsNeed to Be at 12 Min Mark!!!
  • Quick
  • Quick
  • Quick
  • Quick
  • Longer This thesis provided an initial framework to study the ways in which educators may use and inepter score reportsWhen statistical literacy educators are okay When it comes to describing and summarising a score report educators are also okay Variability is more prevalent in questioning and proposing an application of score reports – this was not only based on the educators but also based on the design of the reports. In attempting to relate the relationship between statistical literacy to score report design, values and belifes were more viable than education or years of experence for example. I believe that one of the major contributions of this research is to put educators interpretation and use of score reports at the forefront when we are designing our validity arguments, without a claim about educators use then our arguments towards validity are weak. Must be at the 17 mark here Add more here How does it relate to my findings
  • Quick
  • Quick
  • Longer More research needed to examine categories Talk here about the 4 educators who were higher stats and lower score report interpretation
  • Saad Chahine Thesis Presentation Final

    1. 1. An Investigation of Educators’ Data Habit of Mind <br />A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy, Graduate Department of Human Development and Applied Psychology, OISE/UT <br />Saad Chahine <br />
    2. 2. Rationale<br />External pressures for educators to use data from large- scale assessments<br />Very little is known about the process by which educators interpret and make judgments based on reports from large-scale testing<br />Potential compromise in validity when educators interpret and make judgments about students from large-scale assessment reports<br />2<br />
    3. 3. Literature Review<br />Proposed Use<br />Validity<br />Score Report Design<br />3<br />
    4. 4. Data Habit of Mind <br />4<br />
    5. 5. 5<br />Conceptual Framework <br />
    6. 6. Research Questions <br />RQ1:How are educators proficient in statistical literacy?<br />RQ2:How do educators interpret and propose to use test score reports?<br />RQ3: What are the relationships between statistical literacy and score report interpretations to model Data Habit of Mind?<br />RQ4: How may an educator’s educational history and level of comfort with information, mathematics, and statistics contribute to Data Habit of Mind?<br />6<br />
    7. 7. Methods <br />Designed instruments to measure Statistical Literacy and Score Report Interpretation (2 mock score reports)<br />Conducted pilot test with 12 pre-service students and refined instruments and interview procedure<br />Recruited educators through advertising<br />Conducted cognitive interviews to examine 20 educators’ data habit of mind<br />Used protocol analysis procedure to examine cognitive interview data (i.e., educators’ cognitive processing when interacting with score reports)<br />7<br />
    8. 8. Cognitive Interview Protocol<br />Statistical Literacy Tasks<br />Questions about background & comfort levels with information, statistics & mathematics <br />Cooper’s Score Report<br />Jabberwocky Score Report<br />Educators were asked to verbalize responses and explain their reasoning.<br />8<br />
    9. 9. Protocol Analysis Procedure <br />Stage 1: Recording Verbalizations<br />Stage 2: Transcribing Interviews <br />Stage 3: Segmenting Interviews <br />Stage 4: Encoding Episodes <br />Stage 5: Analysis of the codes <br />Stage 6: Categorizing Educators <br />9<br />
    10. 10. A Snap Shot of the Sample <br />All elementary (Gr. 1-8) teaching experience with provincial testing <br />13 Female, 7 male <br />1-21+ years of experience<br />17 had undergrad focus in Humanities or Social Science and 3 had undergraduate focus in Sciences<br />Majority had B.Ed. (13); others had higher degrees (1 Ph.D., 6 M.Ed.)<br />10<br />
    11. 11. 11<br />RQ1: How are educators proficient in statistical literacy?<br />
    12. 12. 12<br />Statistical Literacy <br />
    13. 13. Results: Statistical Literacy<br />13<br />
    14. 14. 14<br />RQ2: How do educators interpret and propose to use test score reports?<br />
    15. 15. Score Report Interpretation<br />15<br />
    16. 16. Results: Score Report Interpretation<br />16<br />
    17. 17. RQ3: What are the relationships between statistical literacy and score report interpretations to model Data Habit of Mind?<br />17<br />
    18. 18. Results: Data Habit of Mind<br />18<br />
    19. 19. Categories Based on Data Habit of Mind Skills<br />19<br />
    20. 20. Example: Questioning <br />Questioning Patterns for Cooper’s Fitness Test Score Report<br />20<br />
    21. 21. Example: Questioning <br />21<br />Questioning Patterns for Jabberwocky Test Score Report<br />
    22. 22. RQ4: How may an educator’s educational history and level of comfort with information, mathematics, and statistics contribute to Data Habit of Mind?<br />22<br />
    23. 23. Results: Educational History & Comfort Levels<br />Expected that educational history and comfort levels (information, math, and stats) would be meaningfully related to Data Habit of Mind<br />However, found no meaningful relationships…<br />Examination of interview transcripts gives us glimpse of insight into what other factors may be meaningfully related to Data Habit of Mind… <br />23<br />
    24. 24. Educator Beliefs About the Use of Assessment Data<br />Participant E18: “Assessment is probably, for me, has always been in my annual learning goals...my life-long learning goals in my formal years of education. It has been a constant pursuit of mine to understand, advance and implement assessment. We are a very data-driven school and I didn’t have to come to a data-driven school to be hungry for data. It already was in anything that I did...You keep yourself alive by having data. It just goes hand in hand. We are a very…we are a school that is constantly pushing for data.” <br />24<br />Educator with Higher Statistical Literacy and Higher Score Report Interpretation<br />
    25. 25. Participant E13:“I’ve done a few workshops on DRA and reading, in math, like effective instruction. I’ve done a lot of reading myself there and we have had a lot of in-service training. That being said, it is an area that is still a little bit hazy because we are going along in our lessons and I don’t necessarily assess them. We do the evaluation side to see what we can get in marks. That’s why I’m interested in the whole literacy thing because we assess the kids in the reading and see where we need to go from there.”<br />25<br />Educator Beliefs About the Use of Assessment Data<br />Educator with Higher Statistical Literacy and Lower Score Report Interpretation.<br />
    26. 26. Educator Beliefs About the Use of Assessment Data<br />Participant E2:“Ha ha, very high … Well, I think it’s kind of the package, frankly. I have my reading specialist, I have my religion specialist, which is essential for the Catholic school board. I do have a Master’s degree. I also think the fact that I’ve taught all three divisions helps a lot. Um, I am, in fact, I was an adjunct professor, and you have to mentor the young teachers... I’ve gone anywhere from basal readers to whole language to comprehensive literacy. I’ve kind of seen everything. That goes for math education, as well. <br />26<br />Educator with Lower Statistical Literacy and Higher Score Report Interpretation.<br />
    27. 27. Educator Beliefs About the Use of Assessment Data<br />Participant E11: “Assessment to me ... it’s not always like paper and a test, a hard assessment that way. Sometimes I think you can get enough of an assessment by watching, observing and talking to the students. Some might not be able to articulate on paper and pencil what they do by talking.”<br />27<br />Educator with lower Statistical Literacy and Lower Score Report Interpretation.<br />
    28. 28. Discussion <br />This thesis provided an initial framework to understand how educators are interpreting and proposing to use score reports. <br />Findings showed that majority of educators have adequate statistical literacy, and can describe and summarize score reports. <br />However, there was greater variability in educators’ questioning and proposed application of score reports.<br />Educators’ questioning and proposing an application of a report varied across the two score reports and suggests the importance of score report design.<br />Educators’ Data Habit of Mind maybe more related to values and beliefs than level of education, or comfort with information. <br />This framework may potentially be used in building validity arguments. <br />28<br />
    29. 29. Limitations <br />Statistical Literacy tasks were designed for children <br />Score Report Interpretation needs further refining <br />Empirical literature on graphic design and typography lacking <br />Reports were presented on paper <br />No double coding<br />29<br />
    30. 30. Implications <br />Professional <br />Developers <br />Measurement<br /> Specialists <br />B.Ed. Programs<br />30<br />
    31. 31. Future Research <br />More research needed to examine categories <br />Double coding or multiple raters <br />Make links with medical diagnostic methods <br />Include more interactive reporting methods <br />Make links with cognitive human-computer Interface work (e.g., Ware’s work) <br />Conduct large-scale study of reporting systems and improvements<br />31<br />
    32. 32. Thank You <br />32<br />

    ×