Rule Based Expert System for Supporting Assessment of Learning Outcomes

2020 ◽  
Vol 9 (1.2) ◽  
pp. 266-271 ◽  
Keyword(s):  
Expert System ◽  
Learning Outcomes ◽  
Rule Based ◽  
Assessment Of Learning

scholarly journals Adaptation of Kirkpatrick’s Four-Level Model of Training Criteria to Evaluate Training Programmes for Head Teachers

2021 ◽  
Vol 11 (3) ◽  
pp. 116
Author(s):  
Aljawharah Alsalamah ◽  
Carol Callinan
Keyword(s):  
Learning Outcomes ◽  
Evaluation Model ◽  
Training Process ◽  
Educational Training ◽  
Head Teachers ◽  
Female Head ◽  
Assessment Of Learning ◽  
Level Model ◽  
Four Levels ◽  
Training Programmes

Training programmes are evaluated to verify their effectiveness, assess their ability to achieve their goals and identify the areas that require improvement. Therefore, the target of evaluators is to develop an appropriate framework for evaluating training programmes. This study adapted Kirkpatrick’s four-level model of training criteria published in 1959 to evaluate training programmes for head teachers according to their own perceptions and those of their supervisors. The adapted model may help evaluators to conceptualise the assessment of learning outcomes of training programmes with metrics and instruments. The model also helps to determine the strengths and weaknesses of the training process. The adaptation includes concrete metrics and instruments for each of the four levels in the model: reaction criteria, learning criteria, behaviour criteria and results criteria. The adapted model was applied to evaluate 12 training programmes for female head teachers in Saudi Arabia. The study sample comprised 250 trainee head teachers and 12 supervisors. The results indicated that the adapted Kirkpatrick evaluation model was very effective in evaluating educational training for head teachers.

A rule-based poison control expert system

1985 ◽  
Vol 7 (1) ◽  
pp. 33-36 ◽  
Author(s):  
Catherine E. Rubens
Keyword(s):  
Expert System ◽  
Poison Control ◽  
Rule Based

scholarly journals A Belief Rule Based Expert System for Datacenter PUE Prediction under Uncertainty

2017 ◽  
Vol 2 (2) ◽  
pp. 140-153 ◽  
Author(s):  
Mohammad Shahadat Hossain ◽  
Saifur Rahaman ◽  
Ah-Lian Kor ◽  
Karl Andersson ◽  
Colin Pattinson
Keyword(s):  
Expert System ◽  
Rule Based

Graphical Fault Diagnosis Expert System of CNC Machine Tool Based on B/S

2014 ◽  
Vol 945-949 ◽  
pp. 1707-1712
Author(s):  
Bin Shen ◽  
Shu Yu Zhao ◽  
Jia Hai Wang ◽  
Juergen Fleischer
Keyword(s):  
Fault Diagnosis ◽  
Expert System ◽  
Machine Tool ◽  
Case Based Reasoning ◽  
Cnc Machine Tool ◽  
Cnc Machine ◽  
Rule Based ◽  
Detailed Case ◽  
Case Based ◽  
Remote Fault Diagnosis

Based on the authors previous work of developing an expert system for fault diagnosis of CNC machine tool, this paper studied the theory and method of CNC remote fault diagnosis expert system based on B/S, and presents schema and structure of the expert system in detailed. Case based reasoning is used for the multi-alarm diagnosis, and rule based reasoning is used for single-alarm diagnosis. At last fault diagnosis expert system was designed and developed making use of C# and ASP.NET.

Mixed qualitative–quantitative approach for bidding decisions in construction

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Emad Mohamed ◽  
Parinaz Jafari ◽  
Ahmed Hammad
Keyword(s):  
Expert System ◽  
Expert Knowledge ◽  
The Body ◽  
Decision Makers ◽  
Quantitative Approach ◽  
Rule Based ◽  
Content Type ◽  
Factors Affecting ◽  
Qualitative And Quantitative ◽  
Mixed Approach

PurposeThe bid/no-bid decision is critical to the success of construction contractors. The factors affecting the bid/no-bid decision are either qualitative or quantitative. Previous studies on modeling the bidding decision have not extensively focused on distinguishing qualitative and quantitative factors. Thus, the purpose of this paper is to improve the bidding decision in construction projects by developing tools that consider both qualitative and quantitative factors affecting the bidding decision.Design/methodology/approachThis study proposes a mixed qualitative-quantitative approach to deal with both qualitative and quantitative factors. The mixed qualitative-quantitative approach is developed by combining a rule-based expert system and fuzzy-based expert system. The rule-based expert system is used to evaluate the project based on qualitative factors and the fuzzy expert system is used to evaluate the project based on the quantitative factors in order to reach the comprehensive bid/no-bid decision.FindingsThree real bidding projects are used to investigate the applicability and functionality of the proposed mixed approach and are tested with experts of a construction company in Alberta, Canada. The results demonstrate that the mixed approach provides a more reliable, accurate and practical tool that can assist decision-makers involved in the bid/no-bid decision.Originality/valueThis study contributes theoretically to the body of knowledge by (1) proposing a novel approach capable of modeling all types of factors (either qualitative or quantitative) affecting the bidding decision, and (2) providing means to acquire, store and reuse expert knowledge. Practical contribution of this paper is to provide decision-makers with a comprehensive model that mimics the decision-making process and stores experts' knowledge in the form of rules. Therefore, the model reduces the administrative burden on the decision-makers, saves time and effort and reduces bias and human errors during the bidding process.

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