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Motivating Urban Minority Students Through Error Analysis An Action Research Study

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Motivating Urban Minority Students Through Error Analysis An Action Research Study Serigne Gningue (Co-PI) & Julissa Soriano (Noyce Scholar) NSF Robert Noyce Teacher ... – PowerPoint PPT presentation

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Title: Motivating Urban Minority Students Through Error Analysis An Action Research Study


1
Motivating Urban Minority Students Through Error
Analysis An Action Research Study
  • Serigne Gningue (Co-PI) Julissa Soriano (Noyce
    Scholar)
  • NSF Robert Noyce Teacher Scholarship Program
    Conference,
  • Washington, DC May 31, 2013

2
Noyce Program at Lehman College
  • Funds senior undergraduate year and masters
    degree.
  • Mathematics and science teachers from the Bronx
    area commit to 6 years in high needs middle
    schools.
  • Full-year pre-service internship in Bronx middle
    schools.
  • Graduate courses co-taught by science,
    mathematics, and education faculty.
  • Emphasis on formative assessment strategies.

3
Noyce Program Study
  • What challenges and concerns have the Noyce
    Scholars experienced during their first year in
    high needs classrooms?
  • What strategies have the Scholars employed to
    improve their effectiveness?
  • How might the pre-service portion of our program
    be modified to better prepare teachers?

4
New Teacher Challenges
  • Classroom Issues
  • Lack of preparedness for classroom management
  • Lack of preparedness for students level of
    poverty
  • Administrative Tensions
  • Chaotic nature of administration
    priorities/directives
  • Parental Involvement
  • Assessment
  • Chronic Absenteeism
  • 34 of secondary students miss at least 1 month
    of school (NY Times, 7/16/11)

5
Introduced the Following Action Research Model
6
  • Background
  • Power in learning through discovery.
  • Students are not capable to correct their
    misconceptions through the coaching or assistance
    of someone else.

7
Context
  • FDA
  • 81 free lunch
  • 7 Limited English Proficiency (LEP).
  • 41 Hispanic, 57 Black

8
  • What I Found During
  • My First Year of Teaching
  • There is a problem of student achievement,
    interest, motivation, and confidence, and overall
    attitude towards math.
  • Students have difficulty mastering higher-level
    mathematical skills.
  • Students perform poorly on assessments of
    critical thinking skills, formal deduction, and
    proof writing.

9
The Process of S.E.A.
  • Allows students to discover their own mistakes
    and misconceptions
  • Requires the learner to fix the mistake, thus
    forcing the student to dig deeper into the
    subject matter and move onto the next level of
    knowledge
  • Gets students to learn to justify their
    reasoning
  • Allows students to question the reasoning of
    others thus allowing the classroom to become a
    stage for mathematical discourse and
    student-centered instruction.

10
Group Work Instructions
  • 1) Look at students work.
  • 2) Identify at least one error.
  • 3) Complete table on page 2.

11
Implementation- Meaningful Groups
  • Color-Coded Cards
  • Cards Represent Ability on Learning Goal
  • Data Tracker
  • Online Resource LearnBop

12
Data Tracker
13
Teacher Error Analysis
  • Students Error
  • Students misconception
  • Common Core Standard addressed by question
  • Intervention (activity) to address the
    misconception

14
Student Error Analysis
  • Group students based on the common error
  • Give samples of the work
  • Have them identify the mistake(s)
  • Correct the mistake(s)
  • Support their reasoning

15
Differentiation
  • Ability
  • Product
  • Scaffolds and Multiple Entry Points
  • Groupings
  • Homogenously
  • Heterogeneously

16
Common Core Standards
  • Data driven instruction
  • Data driven student groupings, differentiation ,
    and scaffolding
  • Each playlist is Common Core aligned
  • Promotes the mathematical practices Construct
    viable arguments and critique the reasoning of
    others
  • Fosters teacher-student and student-student
    discourse

17
The gift that keeps on giving
  • Data can be used in school inquiry teams
  • Future classroom action research

18
  • Purpose
  • Problem Statement
  • To measure the impact of a discourse-integrated
    teaching strategy utilizing Student Error
    Analysis on student achievement and students
    attitude in the field of mathematics.
  • The impact of discussion integrated instruction
    on student achievement.
  • Decreasing number of students pursuing advanced
    courses or careers in the field of mathematics.

19
Research Questions
1 - To what extent does the use of student error
analysis improve students attitude and
motivation in the mathematics classroom?
2 - To what extent does the use of student error
analysis improve students academic performance
in the mathematics classroom?
20
Literature Review
  • The use of incorrect answers and misconceptions.
  • Student Engagement
  • Discourse-based instruction

21
Participants
  • Both groups were given a baseline assessment
  • The experimental group had an overall mean of
    29 of correct responses with 94 of students
    scoring in the 0-74 range and 6 scoring in the
    80-89 range.
  • The control group had an overall mean of 30 of
    correct responses with 95 of the students
    scoring in the 0-74 range, 2.5 scoring in the
    80-89 range and 2.5 scoring in the 90-100
    range.
  • Limited study of 54 students in two ninth grade
    classes
  • The sample is of convenience
  • one 9th grade class -- the experimental group
  • Asecond 9th grade class --the control group.
  • 27 female students
  • 27 male students.

22
Intervention Plan
  • In between the pre- and post-survey, the
    experimental group received two student error
    analysis activities.
  • One more error analysis activity was carried out
    in between the pre- and post-achievement test.
  • The experimental group student error analysis
    activities were used as a strategy.
  • The control group was instructed through a
    traditional method of teachers whole class
    lectures.
  • Pre and Post Attitude Surveys were also given

23
  • The first time, students analyzed one exercise
  • The incorrect answer and procedure were chosen
    from their previous homework and/or class work.
  • The second time, two exercises were analyzed.
  • Each time, common errors in students homework
    were copied onto the smart board.
  • students were then asked to identify the errors
    and explain why they thought there was a
    mistake.

24
Data Collection
  • Four different instruments were used for data
    collection a math attitude survey, a performance
    task, an achievement test, and classroom
    observations.
  • The data obtained from the pre and post tools
    were averaged and analyzed

25
Data Collection Cont.
  • Other instruments were also used as formative
    assessment, such as exit cards and concept
    attainment activities during the experimental
    period.
  • These assessments, however, were used to identify
    patterns in students misconceptions.

26
RESULTS
Research question 1 To what extent does the use
of student error analysis improve students
attitude and motivation in the mathematics
classroom?
  • The overall average of students attitude and
    motivation towards math in the control group
    decreased by 0.02 from pre-to post-survey.
  • there was an increase of 0.37, from pre- to
    post-survey, in students attitudes and
    motivation towards math in the experimental
    group.

27
SURVEY RESULTS CONTROL GROUP
28
SURVEY RESULTS EXPERIMENTAL GROUP
29
Performance Tasks Results
Research question 2 To what extent does the use
of student error analysis improve students
academic performance in the mathematics classroom?
  • The overall average of students performance task
    in the controlled group decreased by 0.33 from
    the pre- to the post-task.
  • Conversely, the data shows an increase of 1.14 in
    students overall performance in the experimental
    group between the pre- and the post-task.

30
PERFORMANCE TASKS
31
PRE- AND POST-TESTS.
  • Both control and the experimental groups showed
    improvement from pretest to the posttest.
  • The control group had a 25.39 increase
  • The experimental group showed a 31.43 increase.

32
TESTS
33
Conclusions Control Group
  • Data suggest a decrease in students attitude and
    motivation towards math when whole-class
    lecturing was used as a teaching strategy.
  • Students performance on higher order thinking
    tasks seemed to decrease.
  • Their test performance slightly increased.

34
Conclusions _Experimental
  • The error analysis as an instructional
    intervention tool seems to have
  • made a significant difference in students
    attitude and motivation towards math
  • improved students mathematical performance on
    higher order thinking tasks
  • improved students performance on regular
    achievement tests.

35
Recommendations
- Use of more precise data analysis methods to
determine if the differences found are of enough
significance.
- Investigate whether error analysis is
appropriate as an effective strategy regardless
of the content being taught.
36
Share Out
  • Any thoughts?
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