Technology-enhanced learning (TEL) of finite state machines (FSMs)
Repetitively question practicing is observed to be a highly effective learning technique. This technique trains the learner to retrieve and apply knowledge learnt. Being able to apply the knowledge is a sign of great understanding to a learning topic. For the technique to be truly beneficial, new qu...
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sg-ntu-dr.10356-752132023-07-07T17:15:56Z Technology-enhanced learning (TEL) of finite state machines (FSMs) Ling, Ping Liang Jong Ching Chuen School of Electrical and Electronic Engineering DRNTU::Engineering Repetitively question practicing is observed to be a highly effective learning technique. This technique trains the learner to retrieve and apply knowledge learnt. Being able to apply the knowledge is a sign of great understanding to a learning topic. For the technique to be truly beneficial, new question should be attempted at each repetition. The need for new questions may be problematic for topics taught in University as the questions may be limited and difficult to find. This hassle in search of questions often lead to the negligence of such effective learning technique. Educator might help by setting questions for learner to practice on. However, the manual creation of question might be time-consuming and worse if the question consists of multiple parts or require graphical representation such as table, figure or chart. Finite State Machine is one topic with questions that, in most case, has many parts and graphical representation to draw. To ease the creation of Finite State Machine questions and provide many of such question for learner revision, this project aims to develop an automatic question generator specifically for Finite State Machine Question. The generator will be able to create various type of questions in the topic. By implementing randomization algorithm in the question generation, a large pool of questions can be set for learner to try out. With this question generator, the time required to create the question can be saved and learner can create and practice on the question anytime and anywhere. Bachelor of Engineering 2018-05-30T03:30:30Z 2018-05-30T03:30:30Z 2018 Final Year Project (FYP) http://hdl.handle.net/10356/75213 en Nanyang Technological University 65 p. application/msword |
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DRNTU::Engineering Ling, Ping Liang Technology-enhanced learning (TEL) of finite state machines (FSMs) |
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Repetitively question practicing is observed to be a highly effective learning technique. This technique trains the learner to retrieve and apply knowledge learnt. Being able to apply the knowledge is a sign of great understanding to a learning topic. For the technique to be truly beneficial, new question should be attempted at each repetition. The need for new questions may be problematic for topics taught in University as the questions may be limited and difficult to find. This hassle in search of questions often lead to the negligence of such effective learning technique. Educator might help by setting questions for learner to practice on. However, the manual creation of question might be time-consuming and worse if the question consists of multiple parts or require graphical representation such as table, figure or chart. Finite State Machine is one topic with questions that, in most case, has many parts and graphical representation to draw. To ease the creation of Finite State Machine questions and provide many of such question for learner revision, this project aims to develop an automatic question generator specifically for Finite State Machine Question. The generator will be able to create various type of questions in the topic. By implementing randomization algorithm in the question generation, a large pool of questions can be set for learner to try out. With this question generator, the time required to create the question can be saved and learner can create and practice on the question anytime and anywhere. |
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Jong Ching Chuen |
author_facet |
Jong Ching Chuen Ling, Ping Liang |
format |
Final Year Project |
author |
Ling, Ping Liang |
author_sort |
Ling, Ping Liang |
title |
Technology-enhanced learning (TEL) of finite state machines (FSMs) |
title_short |
Technology-enhanced learning (TEL) of finite state machines (FSMs) |
title_full |
Technology-enhanced learning (TEL) of finite state machines (FSMs) |
title_fullStr |
Technology-enhanced learning (TEL) of finite state machines (FSMs) |
title_full_unstemmed |
Technology-enhanced learning (TEL) of finite state machines (FSMs) |
title_sort |
technology-enhanced learning (tel) of finite state machines (fsms) |
publishDate |
2018 |
url |
http://hdl.handle.net/10356/75213 |
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1772825485371244544 |