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Video-Based Analysis of Lesson Structures Lasse Savola, PhD Fashion Institute of Technology—SUNY New York, NY

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Page 1: Video-Based Analysis of Lesson Structures Lasse Savola, PhD Fashion Institute of Technology—SUNY New York, NY

Video-Based Analysisof Lesson Structures

Lasse Savola, PhDFashion Institute of Technology—SUNYNew York, NY

Page 2: Video-Based Analysis of Lesson Structures Lasse Savola, PhD Fashion Institute of Technology—SUNY New York, NY

Doctoral dissertation

The method of lesson structure analysis was introduced in my PhD thesis entitled Video-based analysis of mathematics classroom practice: Examples from Finland and Iceland

Teachers College, Columbia University, 2008

Page 3: Video-Based Analysis of Lesson Structures Lasse Savola, PhD Fashion Institute of Technology—SUNY New York, NY

Large studies using lesson structure analysis

Search for structure in diversity Trends in International Mathematics and

Science Study (TIMSS) (1995, 1999) In 1999, 638 classes in 7 countries

participated Study found that there are many paths to

success The Learner’s Perspective Study (LPS)

(2006) More qualitative in nature Focused on lesson events, not the whole

lessons

Page 4: Video-Based Analysis of Lesson Structures Lasse Savola, PhD Fashion Institute of Technology—SUNY New York, NY

Benefits of video in classroom research

1. Enables the study of complex social processes

2. Helps eliminate the say/do discrepancy

3. Lessens recorder bias

4. Increases inter-coder reliability

5. Permits unlimited reanalysis

Page 5: Video-Based Analysis of Lesson Structures Lasse Savola, PhD Fashion Institute of Technology—SUNY New York, NY

Benefits of video in classroom research

6. Allows for multiple viewpoints 7. Facilitates integration of qualitative and

quantitative methods

8. Enables richer reporting of results

9. Exposes mechanisms and antecedents

10. Can be reduced to lesser forms of event portrayal

Page 6: Video-Based Analysis of Lesson Structures Lasse Savola, PhD Fashion Institute of Technology—SUNY New York, NY

Video in professional development of educators

1. Illustrate various levels of thinking

2. Highlight effective practices

3. Show examples of student misconceptions

4. Provoke conversations about a problematic

teaching moment

5. Focus on specific aspects of teaching

6. Provide a “common ground” experience

Page 7: Video-Based Analysis of Lesson Structures Lasse Savola, PhD Fashion Institute of Technology—SUNY New York, NY

Video in professional development of educators

7. Contrast cases

8. Provide visions of what is possible

9. Compress experience

10. Support role-playing

11. Predict/see what happens

12. Build categories of pedagogical phenomena

13. Enable leaps in time scales

(Pea & Hay, 2003)

Page 8: Video-Based Analysis of Lesson Structures Lasse Savola, PhD Fashion Institute of Technology—SUNY New York, NY

Problems with video analysis

1. Verisimilitude and camera effects

2. Privacy and confidentiality

3. Educational colonialism

4. May be too persuasive, “seductive”

5. Missing contextual information

6. Evaluation of video research

Page 9: Video-Based Analysis of Lesson Structures Lasse Savola, PhD Fashion Institute of Technology—SUNY New York, NY

Why Finland and Iceland?

Cultural and political similarities

In PISA 2006, Finland ranked #1 in mathematics and science, #2 in reading

Despite spending lots of money per student, Iceland’s scores were below average in reading and science and just above average in mathematics

Icelandic gender “problem”

Page 10: Video-Based Analysis of Lesson Structures Lasse Savola, PhD Fashion Institute of Technology—SUNY New York, NY

PISA: Finland and Iceland

2000 2003 2006480

490

500

510

520

530

540

550

560

570

FIN-MathematicsFIN-ReadingFIN-ScienceICE-MathematicsICE-ReadingICE-Science

Page 11: Video-Based Analysis of Lesson Structures Lasse Savola, PhD Fashion Institute of Technology—SUNY New York, NY

Methodology

Twenty schools—ten in each country—participated

Two lessons per teacher were analyzed, although often three were taped

Two cameras in the back of the classroom

Lesson structure analysis using Videograph

Page 12: Video-Based Analysis of Lesson Structures Lasse Savola, PhD Fashion Institute of Technology—SUNY New York, NY

Lesson structure analysis

Two dimensions: Function and Form

The pedagogical functions of lesson elements are based on Herbart’s (1835) cyclical sequence of learning steps (review, lesson, practice)

The categories for the forms of classroom interaction are sample-sensitive and stem from asking: Who is doing what? How are the participants interacting?

Page 13: Video-Based Analysis of Lesson Structures Lasse Savola, PhD Fashion Institute of Technology—SUNY New York, NY

Lesson structure analysis

The first pass categories are fixed (review, introducing new material, practice, other), the second pass categories are sensitive to the sample

The method offers a way to investigate the different forms of classroom interaction by which teachers attempt to achieve their pedagogical goals

One of the strengths of this open-ended method is its ability to capture unique, yet often subtle classroom practices

Page 14: Video-Based Analysis of Lesson Structures Lasse Savola, PhD Fashion Institute of Technology—SUNY New York, NY

Lesson structure analysis

Page 15: Video-Based Analysis of Lesson Structures Lasse Savola, PhD Fashion Institute of Technology—SUNY New York, NY

Research questions

Does the video-based method of lesson structure analysis presented in this report extend the sensitivity of existing methods of lesson structure analysis such as those used in the TIMSS and LPS studies?

Does the video-based method of lesson structure analysis presented in this report permit structural comparison of Finnish and Icelandic mathematics lessons?

Is it feasible to conduct meaningful video-based pedagogical research on a small scale?

Page 16: Video-Based Analysis of Lesson Structures Lasse Savola, PhD Fashion Institute of Technology—SUNY New York, NY
Page 17: Video-Based Analysis of Lesson Structures Lasse Savola, PhD Fashion Institute of Technology—SUNY New York, NY

Some findings

Despite the small sample size, some national patterns and cross-national differences were detected

The Finnish lessons essentially followed the conventional Review-Lesson-Practice-script, whereas more than half of the Icelandic lessons exhibit versions of Individualized learning, a learner-based instructional philosophy

Finnish lessons exhibited more classroom interaction, while many Icelandic lessons consisted only of one-on-one tutoring and no whole-class interaction

Page 18: Video-Based Analysis of Lesson Structures Lasse Savola, PhD Fashion Institute of Technology—SUNY New York, NY

First-pass categories

0%

10%

20%

30%

40%

50%

60%

70%

Review New content Practice Other

FIN(n=20)

ICE(n=20)

Eleven Icelandic lessons were conducted using versions of Individualized learning.

Page 19: Video-Based Analysis of Lesson Structures Lasse Savola, PhD Fashion Institute of Technology—SUNY New York, NY

First-pass categories

The difference in New content is statistically significant.

0%

10%

20%

30%

40%

50%

60%

Review New content Practice Other

FIN(n=20)

ICE*(n=9)

Page 20: Video-Based Analysis of Lesson Structures Lasse Savola, PhD Fashion Institute of Technology—SUNY New York, NY

Forms of Review

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

Teacher presents Students on the board Class works together

FIN(n=20)

ICE*(n=9)

Page 21: Video-Based Analysis of Lesson Structures Lasse Savola, PhD Fashion Institute of Technology—SUNY New York, NY

Forms of IntroducingNew Content

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

Teacher

presents

Series of

connected

questions

Students

work, teacher

helps

Students copy

text

Students read

FIN(n=20)ICE*(n=9)

Page 22: Video-Based Analysis of Lesson Structures Lasse Savola, PhD Fashion Institute of Technology—SUNY New York, NY

Forms of Practicing/Applying

0%

10%

20%

30%

40%

50%

60%

70%

80%

Teacher

discusses

Students work,

teacher helps

Students work,

teacher does not

help

Class works

together

FIN(n=20)

ICE*(n=9)

Page 23: Video-Based Analysis of Lesson Structures Lasse Savola, PhD Fashion Institute of Technology—SUNY New York, NY

Forms of Individualized learning

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

Kikan-Shido Teacher in front Student in front

Page 24: Video-Based Analysis of Lesson Structures Lasse Savola, PhD Fashion Institute of Technology—SUNY New York, NY

Individualized learning

Should not be minimally-guided (Cognitive load theory)

Could be a factor in the decline of Icelandic students’ academic achievement scores

Could be a factor in the Icelandic gender question

Page 25: Video-Based Analysis of Lesson Structures Lasse Savola, PhD Fashion Institute of Technology—SUNY New York, NY

Publication

Sriraman, Bergsten, Goodchild, Michelsen, Palsdottir, Steinthorsdottir, & Haapasalo (Eds.). (2009). The Sourcebook in Nordic Research in Mathematics Education. Charlotte, NC: Information Age Publishing

“…the first comprehensive and unified treatment of historical and contemporary research trends in mathematics education in Scandinavia.”

Page 26: Video-Based Analysis of Lesson Structures Lasse Savola, PhD Fashion Institute of Technology—SUNY New York, NY

Selected resources

Clarke, Emanuelsson, Jablonka, & Mok (Eds.). (2006). Making connections: Comparing mathematics classrooms around the world. The Netherlands: Sense Publishers

Goldman, Pea, Barron, & Derry (Eds.). (2007). Video research in the learning sciences. Mahwah, NJ: Lawrence Erlbaum Associates

Hiebert et al. (2003). Teaching mathematics in seven countries: Results from the TIMSS 1999 video study. US Department of Education

Pea & Hay. (2003). Report to the NSF: CILT Workshop on digital video inquiry in learning and education, 11/25-26, 2002. Stanford, CA: Stanford University

Page 27: Video-Based Analysis of Lesson Structures Lasse Savola, PhD Fashion Institute of Technology—SUNY New York, NY

URL

www.ru.is/lasse