Program Educational Objectives Definition and Assessment for Accreditation Purposes

Abbadeni, Noureddine; Ghoneim, Ahmed; Alghamdi, Abdullah

doi:10.3991/ijep.v3i3.2777

Cited by 11 publications

(13 citation statements)

References 4 publications

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“…Despite the key importance of knowledgeable development of PEOs, SOs, and the mapping between them, there is a lingering confusion, among practitioners, related to them and their correlations. The drastic consequences of such confusion are poor design of curriculum and teaching strategies and a misleading assessment of PEOs and ultimately inaccurate corrective plan . There are several contributing factors to this confusion, among which the lack of adequate knowledge of these components and their correlations and the ambiguity in their terminologies and wordings are the most prominent .…”

Section: Introductionmentioning

confidence: 99%

A data‐mining‐based approach to informed decision‐making in engineering education

Yahya

Osman

2019

Comp Applic In Engineering

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In outcome‐based academic programs, Program Educational Objectives (PEOs) and Student Outcomes (SOs) are two cores around which all programs’ components and processes revolve. Needless to say, the PEOs‐SOs mapping is very critical for program success and, therefore, a deep understanding of PEOs, SOs, and their intra/inter‐correlations is very important for effective program's decisions making. In this context, this paper proposes a data mining‐based approach to discover hidden knowledge of PEOs, SOs, and their mapping and correlations in engineering programs. More specifically, the proposed approach employs association rule mining techniques to generate association rules, among and between PEOs and SOs, from PEOs‐SOs mapping data of a set of engineering programs, which can be then filtered and manipulated to discover the desired knowledge. To this end, a set of 152 self‐study reports of engineering programs, accredited by American Board for Engineering and Technology‐Engineering Accreditation Commission (ABET‐EAC), are collected and the mapping data between their PEOs and ABET‐EAC SOs are extracted. The dataset is processed and transformed into a representation suitable for association rules mining. This involves developing a set of PEOs labels, annotating data with PEOs labels, and extracting three target datasets. Apriori algorithm is then applied to each dataset to generate three sets of association rules. The generated association rules are then filtered and manipulated to discover the knowledge of PEOs, ABET‐EAC SOs, and their mapping and correlations. Finally, a discussion on the informativeness of the discovered knowledge for the decisions making in engineering education is given.

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Section: Introductionmentioning

confidence: 99%

A data‐mining‐based approach to informed decision‐making in engineering education

Yahya

Osman

2019

Comp Applic In Engineering

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“…He also describes three course assessment tools that supports the approach. While (Abbadeni et al, 2013) reviews the existing processes for evaluating PEO's at the Electrical and Computer Engineering Department (ECE) of Lafayette College. The author is then comparing the implemented processes with other institutions and demonstrates the lessons learned of evaluating the PEO's at Lafayette's ECE Department.…”

Section: Background and Related Workmentioning

confidence: 99%

Model-Driven Framework for Evaluating Learning Outcomes Process

Alhaj¹,

Sharah²

2020

Journal of Computer Science

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Evaluating learning outcomes in academic institution can be complex and challenging. Several quantitative and qualitative assessment approaches have been adopted to enhance the process of managing, measuring and visualizing the learning outcomes. The difficulty of implementing and analyzing the evaluation process is mainly caused by the nature of the raw data used in assessment. The data is usually unstructured, complex, text-heavy and collected in high volumes. It may also be extracted from heterogeneous platforms and require privileged accessibility. Using paper-based assessment, such as rubric, in complex evaluation process may cause error prone, confusion in analyzing the learning outcomes and subject to different interpretations of the assessment by academic constituencies. In this study, we propose a model-driven framework for evaluation process of the learning outcomes. The framework has four activities: The data collection and data processing activities are used to extract complex data into a useful information for assessment. The model-driven assessment activity is used to generate and analyze goal models of the learning outcomes in a formal way and allows the assessment at different level of academic institutions. Finally, the evaluation reporting activity is used to generate reports that summarizes the institutional status, metrics and real-time data in a form visual object. A prototype implementation of the framework is evaluated using a case study of an ongoing project at Al-Ahliyya Amman University.

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“…This response showed that the respondent disagreed that using the self-review audit to measure PEOs due to the items in the self-review audit were not purposely to measure the PEOs. PEOs measurement should have been done via more suitable mechanisms such as advisory board meeting, focus group survey, alumni survey, and employer survey (Abbadeni et al, 2013).…”

Section: Polytechnic Employer Survey Identify Employer's Needs and Pementioning

confidence: 99%

“…This response showed that the stakeholders' view is very crucial. According to Abbadeni et al (2013), industrial and societal demands play an important role in forming and building the programme outcomes. Institution has the responsibilities for meeting the needs, interests, and viewpoints of the stakeholders (Asiyai, 2014).…”

Section: Polytechnic Employer Survey Identify Employer's Needs and Pementioning

confidence: 99%

Identifying Instruments to Measure Programme Educational Objectives (PEO) Achievement in Malaysia

Hairi¹,

Affandi²,

Nasri³

2019

ujer

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Outcome Based Education (OBE) is required to be implemented in all academic programmes in Malaysia in order to fulfil the standards specified by the Malaysian Qualification Agency (MQA). One part of the OBE that needs to be measured is Programme Educational Objectives (PEOs). PEOs are broad statements that describe the expected achievement of graduates within three to five years of graduation. All institutions in Malaysia need to measure the PEOs. However, the PEOs of community colleges are not measured yet after five years of programme's implementation. Therefore, this paper systematically reviews the current instruments applied by community colleges in Malaysia to evaluate the programmes and identify the problems in the instruments. This survey study adopted triangulation approach where the data were collected from semi-structured interviews and document analysis. Semi-structured interviews were conducted with five officials from different divisions in the Department of Polytechnic and Community Colleges Education (JPPKK). These samples were purposively selected because their scope of the task was directly involved with the process of development and evaluation of the programme outcomes. Analysis of PEOs was also conducted to compare the PEOs of community college with eight local universities which are UKM, USM, UPM, UTM, UTHM, UTeM, UniMAP and UiTM. The analysis is based on PEOs of engineering or technology program from each institution. The results of this study identified four problems from the community college's instruments which are: (1) no specific measurement of PEOs, (2) unsuitable timeframe of data collection, (3) respondents' feedback is distracted by too many questions, and (4) lack of stakeholders' point of view. These results indicate that community colleges need the right instrument to measure the achievement of PEOs. Therefore, further research is suggested to study the instrument to measure the achievement of community college's PEOs.

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Program Educational Objectives Definition and Assessment for Accreditation Purposes

Cited by 11 publications

References 4 publications

A data‐mining‐based approach to informed decision‐making in engineering education

A data‐mining‐based approach to informed decision‐making in engineering education

Model-Driven Framework for Evaluating Learning Outcomes Process

Identifying Instruments to Measure Programme Educational Objectives (PEO) Achievement in Malaysia

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