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Record W2623584390

Using Feedback from Struggling Readers Reveals a Built-In Lesson

2006· article· en· W2623584390 on OpenAlexaff
Susan M. Kershaw

Bibliographic record

VenueeScholarship (California Digital Library) · 2006
Typearticle
Languageen
FieldPsychology
TopicReading and Literacy Development
Canadian institutionsRoyal Canadian Navy
Fundersnot available
KeywordsGrounded theoryReading (process)Class (philosophy)FeelingCurriculumPsychologyMathematics educationPedagogyQualitative researchStyle (visual arts)Social psychologySociologyComputer scienceLinguisticsVisual arts
DOInot available

Abstract

fetched live from OpenAlex

Using Feedback from Struggling Readers Reveals a Built-In Lesson Susan M. Kershaw (skershaw@rcn.com) Center for Education, Widener University One University Place, Chester, PA 19013 USA Keywords: Struggling readers; differentiated learning; reading strategies; computer-aided instruction. In addition, the interviews served as a way to follow-up on student responses from the class-level measures. Introduction Results and Discussion Students in K-12 are rarely asked their opinions concerning their class curriculum. In particular, struggling readers are usually placed in a specific, highly scripted program, which neither acknowledges these students’ ideas nor the teacher’s expertise. As these students progress from grade level to grade level and through program to program, the probability of anyone asking about their views becomes even more unlikely. Strauss and Corbin (1990) stress the importance of seeking the opinions of students and teachers. The qualitative methodology of grounded theory was used to research the question: How do struggling readers in an 8 th grade “Reading/Enrichment” class feel about the interventions and delivery methods used in their class curriculum? Grounded theory involves interviews, observations, and conversations to understand what is occurring in a particular situation and with the people in that situation (Glaser & Strauss, 1967). The research question lends itself to grounded theory because the process involves an emphasis on comprehending the subjects’ feelings. The results of the Barsch Learning Style Inventory, Reading Surveys, and observations of the students’ behavior gave a picture of this 8 th grade class as struggling readers who displayed various affective behaviors because they, for the most part, said they do not like to read. On the other hand, interviews and other conversations revealed that many of the students did enjoy recreational reading. In addition to their predominately auditory learning style providing a good description of their behaviors, it also helped the teacher to provide classroom instruction that incorporated their learning style. In particular, games where they were able to talk and hear repetition of the target learning items were successful. Considering the data collected and a desire to give students a say in the classroom pedagogy, some adjustments were made. Students had many opportunities to voice their feelings. Some curriculum changes were made, such as literature choice (reading plays). However, students’ suggestions to just talk and not read could not be implemented as the aim of the class is to provide reading instruction. The results of this research suggest that students’ opinions about interventions and delivery methods are important to gather not only for informing instruction, but also as a way of letting students know that their feelings are valued. Other findings include that differentiated learning needs to be used to enable students’ success in the classroom. Teachers’ delivery also needs to be positive and provide repetition. A theme to consider is that classroom research provides a deeper lesson for students via the modeling of self-renewal and its accompanying hard work. This built-in lesson should be explicitly shared with students, especially struggling learners, because it is a life lesson that impacts more than a Reading/Enrichment class. Method th Sixteen 8 grade students (seven boys, nine girls) participated in this study. The students were from a school population that consisted of 1470 students. Over 70% of the student body was below poverty level. The 16 students were placed in a Title I class and had 5 th grade or lower reading levels. Multiple methods were used to assess student opinions of the interventions and delivery methods used in the classroom. Daily observations of the students were conducted by the author. For example, students provided reactions to a reading software program or commented to the author about wanting to do something fun, that is, not read. In addition, students completed the Barsch Learning Style Inventory (Barsch, 1991) and two reading surveys. The Barsch Learning Style Inventory consists of statements that students label as often true, sometimes true, or seldom true of their learning. Based on their responses, students are categorized as visual, auditory, or kinesthetic learners. In the two reading surveys, the students answered questions concerning their reading preferences, including questions about what they liked to read and the number of books they owned. In addition to the class-level measures, individual interviews were conducted with two students to obtain richer information about students’ reactions to reading materials and teacher practices (Goetz & LeCompte, 1984). References Barsch, J. (1991). Barsch learning style inventory. Novato, CA: Academic Therapy Publications. Glaser, B.G., & Strauss, A.L. (1967). The discovery of grounded theory: Strategies for qualitative research. New York: Aldine Publishing Company. Goetz, J.P., & LeCompte, M.D. (1984). Ethnography in qualitative design in educational research. San Diego: Academic Press. Strauss, A., & Corbin, J. (1990). Basics of qualitative research: Grounded theory procedures and techniques. Newbury Park, CA: Sage.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.035
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0060.003

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.035
GPT teacher head0.278
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2006
Admission routes1
Has abstractyes

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