{"id":{"repo_id":"athabasca","oai_identifier":"oai:dt.athabascau.ca:10791/284"},"canonical_url":"https://search.dev.ndltd.org/etd/athabasca/oai:dt.athabascau.ca:10791/284","repository":{"repo_id":"athabasca","name":"Athabasca University","base_url":"https://dt.athabascau.ca/oai/request"},"display":{"title":"AUTOMATIC TEST ITEM GENERATION FROM KNOWLEDGE STRUCTURE","abstract":"2019-01","abstract_html":"2019-01","abstract_has_math":false,"creators":["Aggrey, Ebenezer"],"institution":"Athabasca University","degree_name":"Master of Science, Information Systems (MScIS)","degree_level":"master's","degree_discipline":"Faculty of Science and Technology","degree_department":null,"school":null,"contributors":["Dr Maiga Chang","Dr. Rita Kuo","Dr. Xiaokun Zhang","Dr. Seng Yue Wong"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019-01-16","date_published":"2019-01-16","updated_at":"2026-08-21T16:41:56Z","subjects":["Knowledge Map, Algorithm, Item Generation"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["TC-AEAU-284"],"render_values":[{"text":"TC-AEAU-284","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10791/284","outbound_label":"Handle","outbound_source":"dc:identifier"},"source_record":{"url":"https://dt.athabascau.ca/oai/request?verb=GetRecord&metadataPrefix=oai_etdms&identifier=oai%3Adt.athabascau.ca%3A10791%2F284","prefix":"oai_etdms"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Dr Maiga Chang","Dr. Rita Kuo","Dr. Xiaokun Zhang","Dr. Seng Yue Wong"]},{"key":"dc:creator","label":"Author","values":["Aggrey, Ebenezer"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2019-01-16"]},{"key":"dc:publisher","label":"Institution","values":["Athabasca University"]},{"key":"dc:type","label":"Dc Type","values":["Electronic Thesis or Dissertation"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Faculty of Science and Technology"]},{"key":"thesis:degree_level","label":"Degree Level","values":["master's"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science, Information Systems (MScIS)"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Athabasca University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Knowledge Map, Algorithm, Item Generation"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/10791/284","https://dt.athabascau.ca/jspui/bitstream/10791/284/1/Ebenezer-Aggrey-20190116-V2.pdf","TC-AEAU-284"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["2019-01","This research designs and implements an item generation engine that can automatically create higher order thinking multiple-choice items for online tests based on knowledge maps developed by teachers. Furthermore, this study leveraged questionnaire to collect data from teachers to analyze the agreement between system and participants classification of the cognitive items generated by the algorithms designed and implemented for this study. Results indicated that there are areas where the participants agreed with the systems classification of the cognitive items and in some areas they disagree. However, the system implemented for this research might go a long way to help teachers save the time they need to spend on preparing tests and assessing their students’ understandings of the concepts they have learnt. Moreover, students will benefit from the online test system in terms of having opportunity to self-assess their knowledge at any time and getting rapid test results."]},{"key":"dc:title","label":"Title","values":["AUTOMATIC TEST ITEM GENERATION FROM KNOWLEDGE STRUCTURE"]}]}],"canonical_facts":{"dc:contributor":["Dr Maiga Chang","Dr. Rita Kuo","Dr. Xiaokun Zhang","Dr. Seng Yue Wong"],"dc:creator":["Aggrey, Ebenezer"],"dc:date":["2019-01-16"],"dc:description":["2019-01","This research designs and implements an item generation engine that can automatically create higher order thinking multiple-choice items for online tests based on knowledge maps developed by teachers. Furthermore, this study leveraged questionnaire to collect data from teachers to analyze the agreement between system and participants classification of the cognitive items generated by the algorithms designed and implemented for this study. Results indicated that there are areas where the participants agreed with the systems classification of the cognitive items and in some areas they disagree. However, the system implemented for this research might go a long way to help teachers save the time they need to spend on preparing tests and assessing their students’ understandings of the concepts they have learnt. Moreover, students will benefit from the online test system in terms of having opportunity to self-assess their knowledge at any time and getting rapid test results."],"dc:identifier":["http://hdl.handle.net/10791/284","https://dt.athabascau.ca/jspui/bitstream/10791/284/1/Ebenezer-Aggrey-20190116-V2.pdf","TC-AEAU-284"],"dc:publisher":["Athabasca University"],"dc:subject":["Knowledge Map, Algorithm, Item Generation"],"dc:title":["AUTOMATIC TEST ITEM GENERATION FROM KNOWLEDGE STRUCTURE"],"dc:type":["Electronic Thesis or Dissertation"],"thesis:degree_discipline":["Faculty of Science and Technology"],"thesis:degree_level":["master's"],"thesis:degree_name":["Master of Science, Information Systems (MScIS)"],"thesis:institution_name":["Athabasca University"]},"updated_at":"2026-08-21T16:41:56Z"}