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Record W7009687762

Examining teaching clarity: Student engagement and faculty practice

2012· other· en· W7009687762 on OpenAlexaboutno aff

Bibliographic record

VenueIUScholarWorks (Indiana University) · 2012
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsCLARITYStudent engagementSample (material)Student teacherPerceptionSurvey data collectionHigher education
DOInot available

Abstract

fetched live from OpenAlex

Although clarity of instruction is generally promoted as an effective teaching practice, we know little about how widely students are exposed to this practice in undergraduate education, and even less is known about the extent to which different faculty emphasize clarity in their teaching.In addition, little research has been done to link teaching clarity to other forms of effective educational practice such as student-faculty interaction or active and collaborative learning.This study explores the teaching clarity (TC) behaviors students are exposed to and the extent to which these behaviors relate to student engagement, deep learning, and self-reported gains in college using data from the National Survey of Student Engagement.Using complementary data from the Faculty Survey of Student Engagement, this study further explores TC by examining faculty perceptions of the importance of TC as well as the relationship between TC and faculty use of other effective educational practices. Student Data Source and Sample• The data come from the 2010 administration of the National Survey of Student Engagement • The sample for this study consists of 8102 (41%) first-year students and 11,761 (59%) seniors from 38 baccalaureate granting institutions • The teaching clarity items used in this study were adapted from the Wabash National Study Faculty Data Source and Sample• The data come from the 2011 administration of the Faculty Survey of Student Engagement • The sample for this study consists of nearly 4,400 faculty members from 40 different colleges and universities (two institutions were Canadian) Student ResultsResearch Question 1: What TC behaviors are students exposed to most and least frequently?Percent of Frequently ("Very Often" or "Often") Observed TC Behaviors:Frequencies of teaching clarity items were used to identify which behaviors were "frequently" ("very often" or "often") observed.More frequently observed behaviors were instructors coming to class well-prepared and instructors explaining course goals and requirements clearly.Less frequently observed behaviors include instructors reviewing and summarizing course material effectively and instructors making abstract ideas and theories understandable.Frequencies by disciplinary major fields can be found on our website. Research Question 2: How does TC relate to student engagement?Pearson's r correlations were used to relate the Teaching Clarity Scale to individual NSSE engagement survey items and NSSE Benchmarks of Effective Educational Practice.For both firstyears and seniors, the items with the highest correlations with the Teaching Clarity scale were about students' ratings of their relationships with faculty members, of their institution's emphasis on providing the support they need to succeed academically, and of their entire educational experience at their institution.Correlations between the Teaching Clarity Scale and NSSE Benchmarks can be found below (p < .001).Information about the NSSE Benchmarks can be found on our website. Research Question 3: How does TC relate to deep learning and students' reports of gains in college?Multivariate OLS regressions were used to measure the relationship between the Teaching Clarity scale and measures of deep learning and student-reported gains.The unstandardized coefficients represented below can be interpreted as effect sizes.For both first-years and seniors, the strongest relationships occur between the Teaching Clarity scale and student self-reported gains in college.More information about the scales used in this analysis as well as regression results by major disciplinary field can be found on our website.OLS regression models controlled for gender, transfer status, enrollment status, fraternity or sorority membership, athletic participation, race or ethnicity, primary major field, grades, firstgeneration status, age, institutional control, and institutional Carnegie Classification.All variables standardized before entry into models.Key: all p < .001;+ unstd B > .2,++ unstd B > .3,+++ unstd B > .4,++++ unstd B > .5. Faculty Results Research Question 1: What TC behaviors do faculty find most and least important?Percent "Very Much" or "Quite a Bit" Importance for Faculty TC Behaviors:Frequencies of teaching clarity items were used to identify which behaviors were "very much" or "quite a bit" important to faculty.Clearly explaining course goals and requirements and teaching course sessions in an organized way were among the most important behaviors for faculty and among the most frequently observed behaviors for students.With 13% of faculty finding the use of a variety of teaching techniques to accommodate different learning styles to be "very little" or "somewhat" important, this could be considered the least important TC behavior.Generally, however, all behaviors were found to be important to most faculty.Although using examples or illustrations to explain difficult points was one of the most important behaviors for faculty, the least frequently observed behavior for students was making abstract ideas and theories understandable.This could point to a disconnect between students and faculty-faculty may be providing good examples, but students may still not be understanding.This underlines the importance of formative assessment as a part of the teaching and learning process. Research Question 2: Which faculty have moderate, high, and very high perceptions of the importance of TC?Faculty scores on the FTC scale (items D through I) were divided into three different groups to differentiate between faculty use of moderate (on average 'some' to 'quite a bit' important), high (on average 'quite a bit' important), or very high importance (on average 'very much' important) placed on these teaching clarity behaviors.Representation was as follows:

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)0.009
metaresearch head score (Gemma)0.049
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.049
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0040.002
Open science0.0010.005
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.062
GPT teacher head0.302
Teacher spread0.240 · 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
Published2012
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