Effective Teaching: The Students’ Perspective

Ieta, Adrian; Doyle, Thomas E.; Pallone, Arthur

doi:10.18260/1-2--4318

Cited by 3 publications

(12 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A quantitative degree of correlation among Q1, Q3, and Q4 is also attempted now. This study comes as a second step, with the purpose of confirming, consolidating, and refining the initial conclusions derived in [11].…”

Section: Table 1 Set Questions Investigated Q1mentioning

confidence: 81%

“…However, the frequency of their appearance in the survey does not tell anything about their perceived weight on student perception. Their precise relative weight could not be estimated from the data in [11]. The analysis also suggests that Q1, Q3, and Q4 do not test independent variables but rather correlated ones.…”

Section: Table 1 Set Questions Investigated Q1mentioning

confidence: 91%

“…Following the analysis of the survey data, relevant factors were identified [11] specifically for each question Q1-Q4 (please see Tables 2 to 5). These identified subjective factors were ordered according to the frequency of received answers.…”

Section: Table 1 Set Questions Investigated Q1mentioning

confidence: 99%

“…The present study particularly addresses the above mentioned issues in [11] and attempts to determine a quantitative relative weight of the subjective factors identified. A quantitative degree of correlation among Q1, Q3, and Q4 is also attempted now.…”

Section: Table 1 Set Questions Investigated Q1mentioning

confidence: 99%

“…Our contribution to the investigation of SET as a measure of the quality of instruction is related to what we consider as the source of SET responses, namely the students' relative short term perceptions and reactions to specific instruction. We focused on our engineering students' perspective on effective teaching and learning in an attempt to identify the variables involved in their perception related to SET questions [11]. The survey was conducted in a 200-level electrical engineering class of 26 students.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Effective Criteria For Teaching And Learning

Ieta¹,

Manseur²,

Doyle³

2009 Annual Conference &Amp; Exposition Proceedings

Self Cite

View full text Add to dashboard Cite

Effective criteria for teaching and learningNew faculty as well as experienced faculty may sometimes face challenges concerning teaching evaluations. Student perception of what is taught and what is learned may be significantly different from the instructor's perception and intention. This may become a problem, since education institutions often use student evaluations of teaching as an important criterion for tenure, promotions, retention, or salary raise purposes. The argument goes that student ratings do not help instructors improve their perception of a class unless supported by professional advice. The questions that tend to be of special interest during the evaluation process are: "the course as a whole was...?"; "the course content was...?"; "the instructor's contribution to the course was...?"; "the instructor's effectiveness in teaching the subject matter was...?". In a previous study, we identified that, in fact, engineering students reacted to more particularly defined criteria associated with each question. Those criteria are confirmed by the present study and a quantitative measure can be established for them. A new hierarchy of the student perceived criteria is developed. We show that the SET questions are not testing independent variables but rather correlated ones. A strong correlation between three out of four SET questions has been confirmed and quantitatively assessed. We also report that students reveal triggering factors that override their normal criteria for assigning SET scores. Authors are hopeful that the study may be of interest to new and established engineering instructors. Furthermore, in order to increase the relevance of our conclusions we are planning to use this pilot study as a guideline for a broader research to be conducted at a handful of universities involving different engineering disciplines.

show abstract

Section: Table 1 Set Questions Investigated Q1mentioning

confidence: 81%

Section: Table 1 Set Questions Investigated Q1mentioning

confidence: 91%

Section: Table 1 Set Questions Investigated Q1mentioning

confidence: 99%

Section: Table 1 Set Questions Investigated Q1mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Effective Criteria For Teaching And Learning

Ieta¹,

Manseur²,

Doyle³

2009 Annual Conference &Amp; Exposition Proceedings

Self Cite

View full text Add to dashboard Cite

show abstract

Capstone Projects: Unleashing Imagination and Engaging Minds

Ieta¹,

ofProfessional²,

Manseur³

2013 ASEE Annual Conference &Amp; Exposition Proceedings

Self Cite

View full text Add to dashboard Cite

is currently the Director of Engineering Development and a member of the Computer Science faculty at SUNY Oswego where he is actively developing a new modern and innovative Electrical and Computer Engineering Program. His academic interests lie in Engineering Education and Engineering Program Development, Robotics, Visualization and Simulation Software Development, and Digital and Embedded System Design. He holds a Ph.D in Electrical Engineering from the University of Florida, an MS degree in EE from the University of Houston, and a licence-es-sciences in Mathematics from the University of Algiers. He is registered as a professional Engineer in the State of Florida and the author of numerous articles in his areas of expertise including the textbook "Robot Modeling and Kinematics" and its associated modeling and visualization software.

show abstract

Tracking Student Success in Order to Assess the Instructor Effectiveness to Improve Student Retention and Graduation Rates

Manteufel,

Karimi

2018 Gulf Southwest Section Conference Proceedings

View full text Add to dashboard Cite

This paper explores the metric of follow-on student success that can be considered when evaluating an instructor's effectiveness. The metric is the follow-on course success rate which should be useful in engineering since many fundamental courses are prerequisites to follow-on courses. For example, students who pass thermodynamics 1 should be able to pass thermodynamics 2. The data shows that the follow-on success rate depends on the instructor who teaches the first course. As more universities focus on student retention and graduation rates, they should investigate metrics to gauge how well an instructor prepares students for subsequent academic success. This paper looks at course follow-on success rate in a two-semester sequence of thermodynamics courses.

show abstract

Effective Teaching: The Students’ Perspective

Cited by 3 publications

References 11 publications

Effective Criteria For Teaching And Learning

Effective Criteria For Teaching And Learning

Capstone Projects: Unleashing Imagination and Engaging Minds

Tracking Student Success in Order to Assess the Instructor Effectiveness to Improve Student Retention and Graduation Rates

Contact Info

Product

Resources

About