An Affective-Cognitive Teaching and Learning Approach for Enhanced Behavioural Engagements among Engineering Students

Lashari, Tahira Anwar; Alias, Maizam; Kesot, Mohd Jahaya; Akasah, Zainal Abidin

doi:10.11120/ened.2013.00011

Cited by 21 publications

(11 citation statements)

References 11 publications

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“…Predicting RBT level of questions starts with the construction of knowledge prediction model with support vector machine classifier. The model takes input as questions obtained from a corpus BCLsDataSet (Lashari et al, 2012). The corpus contains six hundred questions, 100 for each Bloom's Taxonomy level such remember, understand, evaluate, analyze, apply and create.…”

Section: Experimentation and Results Discussionmentioning

confidence: 99%

A Descriptive Analysis of Students Learning Skills Using Bloom’s Revised Taxonomy

Sami

Umamakeswari

2020

Journal of Computer Science

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The academic committees worldwide suggest technical institutions to follow Revised Bloom's Taxonomy (RBT), a framework that helps to develop learning objectives. The model classifies a hierarchy of educational objectives such as cognitive, sensory and affective domains that are not only helping the students to evolve thinking abilities but also to identify the skills they are lacking with. Analysis of students RBT skills through data mining techniques is more valuable and is yet to be explored. This paper employs predictive and descriptive techniques of data mining to analyze the RBT level of each student. The methodology uses a classifier to classify the RBT level of questions under six levels such as remembering, understanding, applying, analyzing, evaluating, creating and performs clustering of students with respect to overall RBT level and lacking RBT skill of each student. The experimentation is carried out with university students. The results show that the proposed classifier is able to achieve 98% accuracy by correctly classifying RBT levels of input questions. The results also shows that the proposed work creates précised and meaningful clusters of overall RBT level/Lacking RBT skill of each student with precision 0.83 and 0.79 which could help the instructor to design different pedagogical approaches to improve students learning.

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Section: Experimentation and Results Discussionmentioning

confidence: 99%

A Descriptive Analysis of Students Learning Skills Using Bloom’s Revised Taxonomy

Sami

Umamakeswari

2020

Journal of Computer Science

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“…Further study is important for developing an integrated cognitive-affective teaching and learning framework in undergraduate SE education to guide undergraduate SE educators. To support this framework, development experimental research that proposes, applies and evaluates an integrated cognitive-affective learning approach with an appropriate control using traditional method can be conducted, as recommended by Lashari et al [35].…”

Section: Discussionmentioning

confidence: 99%

“…Several techniques for promoting affective learning in engineering education, recommended by Alias et al [28], can be implemented during the workshops. These include question and answer sessions, a motivational talk or video, positive reinforcement such as rewarding remarks, to motivate continuous effort in learning, and student-teacher interaction that promotes empathy, modelling, peer learning, and group processing [28], [35].…”

Section: Discussionmentioning

confidence: 99%

The Effectiveness of a Systems Engineering Course in Developing Systems Thinking

2020

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Contribution: An evaluation of the effectiveness of Systems Engineering (SE) courses in developing students' Systems Thinking (ST) capacity in both the cognitive and affective domains. A combined cognitive ST performance and affective engagement with ST assessment is proposed as an approach to assess students' ST in both domains. The results can support course change decisions and guide learning experience development. Background: SE education aims to produce graduates with strong knowledge and skills in SE and a strong appreciation of the practical value of ST, which addresses the cognitive and affective domains in education. Consequently, it is important to evaluate the effectiveness of SE courses in developing students' ST in these domains, an area that studies do not consider. Intended Outcomes: An understanding of the ST ability of undergraduate students in an SE course in a domain specific engineering program in both the cognitive and affective domains. Application Design: A study evaluated the effectiveness of two SE classes in developing students' ST capacity using a combined cognitive and affective assessment tool developed and validated in previous studies. ST assessment is determined by combining ST performance and affective engagement. To observe the transformation of students' ST capacity, a longitudinal design collected data at two times in each of two offerings of an SE course offered by the same university in two locations-Australia and Singapore. Findings: The course developed students in most dimensions of cognitive ST, but did not appear to improve students' affective engagement with ST.

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“…This model's target was primarily the students' mastery and motivation to learn the subject content and secondarily their ability to guide their mastery through moral and ethical development for the betterment and welfare of society. Lashari et al ( 2013 ) attempted an affective-cognitive teaching and learning approach with the intent of increasing student engagement during class. While there is clear recognition that learning domains beyond the cognitive were important, however, the application of the other domains appeared more utilitarian than holistically developmental.…”

Section: Literature Reviewmentioning

confidence: 99%

Final Year Engineering Project and Its Contribution to Holistic Education

Tien

Gamboa

Namasivayam

2015

Taylor’s 7th Teaching and Learning Conference 2014 Proceedings

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The fi nal year project is a crucial component of engineering undergraduate education that is made a compulsory requirement by engineering accreditation bodies worldwide. This paper documents an approach toward the fi nal year engineering project that is consistent with an outcome-based education methodology as required by accreditation bodies but also incorporates the development of a desirable range of graduate capabilities through its unique approach. The method, implementation, measurement of outcomes, and survey fi ndings on the students taking this module are presented in this paper. For the measurement of outcomes, both qualitative and quantitative approaches were utilized. The quantitative approach consisted of using a Likert scale online survey as well as a software tool to capture the marks from various assessment components of the module to use as a comparison. The software tool links these assessment components to the module learning outcomes and the learning domains of Bloom's taxonomy. The marks attained were considered to be refl ective of the attainment of the outcomes. The qualitative approach utilized a written survey that is part of the online survey. This online survey focused on student perceptions assessed through the Likert scale and written feedback instead of marks. The data obtained from both approaches were analyzed and compared, and the fi nal year project module is evaluated for its effectiveness in delivering holistic education. These different approaches substantiated the fi ndings of one another and helped determine to what extent the holistic education outcomes were achieved.

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An Affective-Cognitive Teaching and Learning Approach for Enhanced Behavioural Engagements among Engineering Students

Cited by 21 publications

References 11 publications

A Descriptive Analysis of Students Learning Skills Using Bloom’s Revised Taxonomy

A Descriptive Analysis of Students Learning Skills Using Bloom’s Revised Taxonomy

The Effectiveness of a Systems Engineering Course in Developing Systems Thinking

Final Year Engineering Project and Its Contribution to Holistic Education

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