Technology to TEACH


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This presentation was given by Kathy Maksimov, Curriculum Specialist from the Waterford Institute, at the Pacific District Executive Forum on March 11, 2009. The presentation focused on the ability of well-designed instructional technology to replicate teaching best practices across multiple environments and means of measuring program efficacy.

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  • Technology to TEACH

    1. 1. Technology to TEACH Kathy Maksimov Curriculum Specialist
    2. 2. Modern Computing Technology
    3. 3. Manufacturers needed consistency
    4. 4. Scientists needed perfect recall and delivery
    5. 5. Businesses needed the ability to scale
    6. 6. Turned to Technology Consistent, replicable Perfect recall and delivery The ability to scale
    7. 7. As educators, we need consistency, perfect recall, the ability to scale, and … … the time to focus on just one child.
    8. 8. Our Students <ul><li>Pre-Literacy Training by First Grade </li></ul>Marilyn Jager Adams, Beginning to Read , 1990 Middle Class Low Income 3000 Hours 200 Hours
    9. 9. Our Students Early Predictor
    10. 10. Our Students <ul><li>- Hart and Risley, Meaningful Differences (1995) </li></ul>Welfare Parents 13 million words 2:1 negative to positive Working Class Parents 26 million words 2:1 positive to negative Professional Parents 45 million words 6:1 encouraging Vocabulary at age 4
    11. 11. A normal classroom Average Students Exceptional Students Troubled Students
    12. 12. The Average School Day <ul><li>- Eaton H. Conant (1973) </li></ul>Time at school Actual Instruction Individualized Instruction 7 Hours 2 Hours 1 Minute!
    13. 13. “ The Work Problem” w = p * e <ul><li>w is the work produced by a system </li></ul><ul><li>p is the potential of the system to create work </li></ul><ul><li>e is efficiency of the system in creating work </li></ul>
    14. 14. Efficiency (e) <ul><li>How well workers work. </li></ul><ul><li>Maximum = 100% </li></ul><ul><li>Examples: </li></ul><ul><ul><li>Lesson manuals </li></ul></ul><ul><ul><li>Professional development </li></ul></ul><ul><ul><li>Mastery learning </li></ul></ul><ul><ul><li>Managed schools, charter schools, etc. </li></ul></ul><ul><ul><li>Accountability </li></ul></ul><ul><ul><li>Grouping students </li></ul></ul>
    15. 15. Potential (p) <ul><li>Workers and tools </li></ul><ul><li>Limited only by the worker or tool </li></ul><ul><li>Examples: </li></ul><ul><ul><li>Teacher </li></ul></ul><ul><ul><li>Paraprofessionals </li></ul></ul><ul><ul><li>Manipulatives </li></ul></ul><ul><ul><li>Chalkboards or digital whiteboards </li></ul></ul><ul><ul><li>Books </li></ul></ul><ul><ul><li>Software … </li></ul></ul>
    16. 16. w = p * e Example: Digging a Foundation
    17. 17. The Work Problem What if your students need this much work?
    18. 18. An Ideal Solution? <ul><li>Do I scale? </li></ul><ul><li>Can I individualize? </li></ul><ul><li>Am I interactive? </li></ul><ul><li>Perhaps you just need more of me … </li></ul>
    19. 19. <ul><li>Costs too much … </li></ul><ul><li>Can’t find enough experts … </li></ul><ul><li>Too hard to consistently train existing resources … </li></ul><ul><li>Not enough time … </li></ul>Why can’t we solve the work problem?
    20. 20. The Ideal Solution Described <ul><li>Scalable </li></ul><ul><li>Affordable </li></ul><ul><li>Perfect recall </li></ul><ul><li>Consistently replicable </li></ul><ul><li>Never tired, impatient, or frustrated </li></ul><ul><li>Always the very best performance </li></ul><ul><li>Constantly improving </li></ul>
    21. 21. The Work Problem … What if your students need this much work?
    22. 22. The Work Problem … Solved!
    23. 23. Technology fundamentally changes potential … <ul><li>Communication example: </li></ul><ul><ul><li>Pony Express </li></ul></ul><ul><ul><li>Telegraph (45.4 million times faster than a horse) </li></ul></ul><ul><ul><li>Telephone </li></ul></ul><ul><ul><li>Radio </li></ul></ul><ul><ul><li>Television </li></ul></ul><ul><ul><li>Optical fiber / Internet </li></ul></ul>
    24. 24. Musical Performance <ul><li>A pioneer father goes to see a concert … </li></ul>
    25. 25. Teaching is a Performance <ul><li>What if you could capture and always deliver the best teaching? </li></ul>
    26. 26. The Formation of Waterford - Dusty’s Epiphany
    27. 27. Moore’s Law And so on…
    28. 28. Doubling Checkmate $184,000,000,000,000,000.00
    29. 29. <ul><li>In the beginning, most people only saw a penny. </li></ul>
    30. 30. Decision Science
    31. 31. Learner Profiles <ul><li>Can we apply decision science in education? </li></ul>
    32. 32. Approximation to Precision
    33. 33. Linear vs. Exponential Growth Source: Kurzweil 2005, The Singularity is Near
    34. 34. Leveraging Technology Requires … <ul><li>Commitment </li></ul><ul><li>Willingness to change … </li></ul><ul><ul><li>How we view the classroom </li></ul></ul><ul><ul><li>How we view the role of the teacher </li></ul></ul><ul><ul><li>What we teach and when </li></ul></ul><ul><ul><li>How we use student data </li></ul></ul>
    35. 35. Leveraging Technology Delivers … <ul><li>the very best education </li></ul><ul><li>individualized </li></ul><ul><li>for each student on the curve </li></ul>
    36. 36. A Teacher’s Perspective … “ It’s independently run. I turn it on in the morning and it pretty much through the rest of the day, gives them their time on it and evaluates where they need to be the next day.” - Shannon Skipper, Pre-K Teacher, Gadsen, Alabama
    37. 37. Teacher Experience
    38. 38. > 450 Hours of Instruction
    39. 39. Ways Programs Deliver Instruction Menu Linear / Predetermined Adaptive (Mastery-based) 1 2 3 4 From Chutes and Ladders by Milton Bradley
    40. 40. Waterford Delivers Instruction Automatically individualized for each student From Chutes and Ladders by Milton Bradley
    41. 41. Waterford’s Sequencing Lesson Pre-assessment Song Book Instruction Practice Extended Practice Assessment Did the student master the learning objective?
    42. 42. Sequencing within a Lesson “ Successful” Sara Continue to the next lesson
    43. 43. Sequencing within a Lesson “ Needs Help” Sam Mark this lesson to automatically try again later
    44. 44. Sequencing between Lessons Automatic Review Automatic Review Try Again “ Successful” Sara “ Needs Help” Sam 1 2 3 1 4 1 2 3 2 1
    45. 45. Teacher Reports <ul><li>Averages </li></ul><ul><li>Student progress, usage, and skill performance </li></ul><ul><li>Highlighted areas of concern </li></ul>
    46. 46. Meet “Miss Waterford” <ul><li>One-on-one instruction tailored for each student … </li></ul><ul><li>… Proven methods, endlessly patient, FUN, responsive, private, equitable </li></ul>
    47. 47. The Data <ul><li>Understand types of efficacy studies </li></ul><ul><li>Review examples with Waterford </li></ul>
    48. 48. Understanding Terms <ul><li>Random Assignment : </li></ul><ul><ul><li>a technique for assigning subjects to different treatments (or no treatment). </li></ul></ul><ul><li>Control Group </li></ul><ul><ul><li>the group that does not receive the new treatment being studied. </li></ul></ul>
    49. 49. Study Designs
    50. 50. Quasi Experiments <ul><li>Pretest Posttest Nonequivalent Group .  </li></ul><ul><ul><li>Control and treatment </li></ul></ul><ul><ul><li>Group assignment by convenience </li></ul></ul><ul><ul><li>Pretest and posttest </li></ul></ul>
    51. 51. Commons Lane Elementary <ul><li>Pre and Posttest (Terra Nova) </li></ul><ul><li>Participants (K and 1 st ): </li></ul><ul><ul><li>Commons Lane (treatment) – 20 students per class; approx. 80 </li></ul></ul><ul><ul><li>Halls Ferry (control) – 13 students per class; approx. 80 </li></ul></ul><ul><li>Non-equivalents </li></ul><ul><ul><li>Class size (favors the control) </li></ul></ul><ul><ul><li>Pretest scores (Commons Lane kindergarteners had lower pretest scores) </li></ul></ul>Example
    52. 52. Commons Lane – Kindergarten Results Commons Lane = 3 times the gains! Example
    53. 53. Commons Lane – 1 st Grade Results Commons Lane = 2 times the gains! Example
    54. 54. Hecht and Close (Florida) <ul><li>Pre and Posttest </li></ul><ul><li>Participants: inner city & rural public schools with low SES (“at risk” students) </li></ul><ul><ul><li>42 Kindergarteners (treatment) </li></ul></ul><ul><ul><li>34 Kindergarteners (control) </li></ul></ul><ul><li>Treatment: </li></ul><ul><ul><li>Six months on Reading Level One </li></ul></ul>Example
    55. 55. Hecht and Close - Definitions <ul><li>Effect sizes (ES): tell how different two groups are. </li></ul><ul><ul><li>ES = 0.2: small difference </li></ul></ul><ul><ul><li>ES = 0.5: medium difference </li></ul></ul><ul><ul><li>ES = 0.8: large difference </li></ul></ul><ul><li>Finding : Best Predictors of Future Reading Ability </li></ul><ul><ul><li>Segmenting and blending phonemes </li></ul></ul>Example
    56. 56. Hecht and Close - Results <ul><li> Segmenting ES = 1.14 </li></ul><ul><li> Blending ES = 1.13 </li></ul><ul><li> Word Reading ES = 1.11 </li></ul><ul><li> Invented Spelling ES = 1.19 </li></ul><ul><li> Print Concepts </li></ul><ul><li> Letter Name </li></ul><ul><li> Letter Sound </li></ul><ul><li> Letter Writing </li></ul>“… Computer assisted instruction provides a cost effective way to teach at-risk children.” Example
    57. 57. Hecht and Close - Results <ul><li>Confident in Results: </li></ul><ul><ul><li>Exact amount of time each student used Waterford </li></ul></ul><ul><ul><li>Computer delivers identical experience </li></ul></ul><ul><ul><li>Individualized </li></ul></ul><ul><ul><li>Reports show exactly how students performed </li></ul></ul>Studying Computer-Based Instruction Example Studying Classroom Instruction
    58. 58. Hecht and Close <ul><li>Sited in: Developing Early Literacy: Report of the National Early Literacy Panel </li></ul><ul><li>“ Found that … Amount of exposure children had to [Waterford] contributed to individual differences in phonemic awareness and spelling.” </li></ul>Example
    59. 59. Quasi Experiments <ul><li>Time Series Designs .  </li></ul><ul><ul><li>One group of subjects </li></ul></ul><ul><ul><li>Pretested and posttested at different intervals.  </li></ul></ul><ul><ul><li>The purpose might be to determine long-term effect of treatment and therefore the number of pre- and posttests can vary from one each to many.  </li></ul></ul>
    60. 60. Hillcrest Elementary <ul><li>Demographic: </li></ul><ul><ul><li>Title 1 School (low SES) </li></ul></ul><ul><li>Before Waterford: </li></ul><ul><ul><li>Below district average reading scores </li></ul></ul><ul><ul><li>75% of students were in two lowest reading categories: below basic (more then 50%) and basic </li></ul></ul>Example
    61. 61. Hillcrest Elementary - Results <ul><li>Two years after Waterford: trend reversed. </li></ul><ul><ul><li>75% students in top two categories: Proficient and Advanced </li></ul></ul><ul><li>Three years after Waterford: </li></ul><ul><ul><li>the first class to use all three levels of Waterford from kindergarten to second-grade reached the third-grade and had the highest reading scores of all 36 schools in the district! </li></ul></ul>Example
    62. 62. Hillcrest Elementary - Results Kindergarten Student Rankings on the Utah State Core Assessment Test Number of Students 1996* Example
    63. 63. State of Idaho <ul><li>Participants: 8 Idaho School Districts </li></ul><ul><ul><li>3,394 students (treatment) </li></ul></ul><ul><ul><li>2,413 students (historical control) </li></ul></ul><ul><li>Test scores (IRI) over 4 years </li></ul>Example
    64. 64. State of Idaho – Results More Use = Higher Gains 36 37 38 39 44 49 34 36 38 40 42 44 46 48 50 Control 0–1000 1001– 1500 1501– 2000 2001– 2500 2500+ Usage (Minutes) Average Gain Waterford recommends 15 min per day = 2250 min Example
    65. 65. State of Idaho - Results <ul><li>Lowest third (at-risk) experienced the most gains (>1.0 effect size ). </li></ul><ul><li>Finishing the level had a larger effect size than SES, motivation, and tutoring. </li></ul>Example
    66. 66. A Midwest School (Indiana) <ul><li>Pretest and Posttest </li></ul><ul><li>Participants: </li></ul><ul><ul><li>46 first grade students (year 2001) - Treatment </li></ul></ul><ul><ul><li>47 first grade students (year 2000) - Control </li></ul></ul><ul><li>Historical control is nice because it reduces the variance from teachers. </li></ul>Example
    67. 67. A Midwest School - Results <ul><li>Evaluated students by how they performed on the pretest: </li></ul><ul><ul><li>High scores </li></ul></ul><ul><ul><li>Moderate scores </li></ul></ul><ul><ul><li>Low scores </li></ul></ul><ul><li>All treatment students outperformed their control counterparts … but the low treatment outperformed the moderate control on the posttest! </li></ul>Example
    68. 68. A Midwest School - Results 660 640 620 600 580 560 540 520 500 Grade 1 Grade 2 Control – High Control – Moderate Control – Low Exp – High Exp – Moderate Exp – Low Example
    69. 69. True Experiments <ul><li>“The Gold Standard” </li></ul><ul><li>Random treatment and control </li></ul><ul><li>Testing to measure change in both groups </li></ul><ul><li>Only research method that can adequately measure the cause and effect relationship </li></ul>
    70. 70. True Experiments <ul><li>Post Equivalent Groups. </li></ul><ul><ul><li>Treatment and control </li></ul></ul><ul><ul><li>Randomized assignment to groups </li></ul></ul><ul><ul><li>Posttest administered to measure difference </li></ul></ul>R = Randomized participants N = Not-randomized participants O = Test X = Treatment
    71. 71. True Experiments <ul><li>Pretest Posttest Equivalent Groups </li></ul><ul><ul><li>Treatment and control </li></ul></ul><ul><ul><li>Randomized assignment to group </li></ul></ul><ul><ul><li>Pretest to measure difference before the study takes place </li></ul></ul><ul><ul><li>Posttest to measure effect of treatment </li></ul></ul>R = Randomized participants N = Not-randomized participants O = Test X = Treatment
    72. 72. True Experiments in Education <ul><li>One review showed that not even 1 percent of dissertations in education or of the studies archived in ERIC Abstracts involved randomized experiments. </li></ul>
    73. 73. True Experiments in Education
    74. 74. Challenges for True Experiments in Education <ul><li>Random sample </li></ul><ul><ul><li>Parents </li></ul></ul><ul><ul><li>School staff / Well-meaning teachers </li></ul></ul><ul><li>Fidelity of implementation </li></ul><ul><ul><li>Teacher abilities </li></ul></ul><ul><ul><li>Classroom set up </li></ul></ul><ul><ul><li>Scheduling </li></ul></ul>
    75. 75. Tucson – Math and Science <ul><li>Participants: </li></ul><ul><ul><li>5 Title 1 schools in Tucson Unified School District </li></ul></ul><ul><ul><ul><li>Free and reduced lunch rate 88.5%-97.5% </li></ul></ul></ul><ul><ul><ul><li>22 classrooms </li></ul></ul></ul><ul><ul><ul><li>338 students total </li></ul></ul></ul><ul><ul><li>Treatment and Control </li></ul></ul><ul><ul><li>Random assignment of classrooms </li></ul></ul><ul><ul><li>Pretest and Posttest </li></ul></ul><ul><ul><ul><li>SAT10 Math and the environment (science) tests </li></ul></ul></ul>Example
    76. 76. Tucson Results by classroom 4.95 6.10 11.37 10.44 7.85 Diff 92.6% 97.5% 98.3% 90.6% 88.5% Free & Reduced Lunch 29.1% 6.21 1.26 E WEMS Control 49.0% 13.02 6.92 D WEMS Control 22.5% 14.23 2.86 C WEMS Control 39.2% 13.43 2.99 B WEMS Control 16.0% 8.84 .99 A WEMS Control ELL Gain School Example
    77. 77. Tucson Results define terms <ul><li>NCE (Normal Curve Equivalent) </li></ul><ul><ul><li>Where a student falls on a normal curve </li></ul></ul><ul><ul><ul><li>Indicates a student’s rank compared to other students on the same test </li></ul></ul></ul><ul><ul><li>Range from 1-99 with mean of 50 </li></ul></ul><ul><ul><li>In a normally distributed population, if all students make exactly one year of progress, NCE gain would be zero even though raw score increased. </li></ul></ul>Example
    78. 78. Tucson Results by subject Math Science Example
    79. 79. Tucson Results by gender Example
    80. 80. Tucson Results by ELL status Example
    81. 81. Tucson Results by ELL status Waterford ELL students had the lowest pretest scores and the highest posttest scores! Example
    82. 82. Qualitative Research <ul><li>Uses “naturalistic” methods </li></ul><ul><ul><li>interviewing </li></ul></ul><ul><ul><li>observation </li></ul></ul><ul><ul><li>focus groups </li></ul></ul><ul><li>No statistical or quantitative procedures </li></ul><ul><li>Goals </li></ul><ul><ul><li>behavior in natural setting </li></ul></ul><ul><ul><li>perspective of the research participant </li></ul></ul><ul><ul><li>meanings people give to their experience </li></ul></ul>
    83. 83. Madisonville Consolidated Independent School District <ul><li>Teachers report higher interest in reading </li></ul><ul><ul><li>They report that children now argue over who is allowed to go to the reading centers, when previously there was little interest shown in reading activities. </li></ul></ul><ul><li>Teachers report improved home/school connection; parents support program 100% (survey) </li></ul><ul><li>Increased student academic self-esteem </li></ul><ul><li>Waterford supports and supplements existing curriculum </li></ul><ul><li>Waterford is user friendly </li></ul><ul><li>Anecdotes of improved phonemic awareness and reading readiness skills </li></ul>Example
    84. 84. Questions?