Cecilia Obi Nja, Kimson Joseph Idiege, Uduak Edet Uwe, Anne Ndidi Meremikwu, Esther Etop Ekon, Costly Manyo Erim, Julius Ukah Ukah, Eneyo Okon Eyo, Mary Ideba Anari, Bernedette Umalili Cornelius-Ukpepi
{"title":"人工智能在科学教学中的应用:以非洲科学教师为视角","authors":"Cecilia Obi Nja, Kimson Joseph Idiege, Uduak Edet Uwe, Anne Ndidi Meremikwu, Esther Etop Ekon, Costly Manyo Erim, Julius Ukah Ukah, Eneyo Okon Eyo, Mary Ideba Anari, Bernedette Umalili Cornelius-Ukpepi","doi":"10.1186/s40561-023-00261-x","DOIUrl":null,"url":null,"abstract":"Abstract This study investigated the factors influencing science teachers' 'Artificial Intelligence' (AI) utilization by using the 'Technology Acceptance Model' (TAM). The factors investigated alongside TAM variables were teachers' data like; age, sex, and residence type. TAM items that were correlated in this study included; self-esteem, stress and anxiousness, ease of utilization, behavioural intention, attitude towards AI usage, and expected benefits. The population of this study comprised all science teachers (170) in the Calabar Education Zone of Cross River State, Nigeria. The sample was made up of 79 science teachers comprising (58.22%) 46 females and (41.77%) 33 males. The descriptive and analytical research design was used in this study. A questionnaire named ' Approval of Artificial Intelligence: The Teachers' Eye' Questionnaire (AAITEQ) was used for the study. This study raised 3 research questions. The reliability for AAITEQ was from 0.72 to 0.81 using Cronbach's alpha. Findings indicated that the approval for the utilization of AI was high with an overall mean score of 3.00. The highest predicting value for behaviour intent using TAM variables was the ease of usage r = .789. Science teachers' sex (t, 77 = 1.988; p = .060, ( p ˃ .05), age F (2, 76) = .547; p = .581 ( p ˃ .05) and teachers' residence location (t, .77 = .533; p = − .062 ( p ˃ .05) did not influence the behaviour of science teachers' intention of the utilization of AI. It was recommended that both in-service and pre-service teachers be trained on the utilization of AI.","PeriodicalId":21774,"journal":{"name":"Smart Learning Environments","volume":"29 1","pages":"0"},"PeriodicalIF":6.7000,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Adoption of artificial intelligence in science teaching: From the vantage point of the African science teachers\",\"authors\":\"Cecilia Obi Nja, Kimson Joseph Idiege, Uduak Edet Uwe, Anne Ndidi Meremikwu, Esther Etop Ekon, Costly Manyo Erim, Julius Ukah Ukah, Eneyo Okon Eyo, Mary Ideba Anari, Bernedette Umalili Cornelius-Ukpepi\",\"doi\":\"10.1186/s40561-023-00261-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract This study investigated the factors influencing science teachers' 'Artificial Intelligence' (AI) utilization by using the 'Technology Acceptance Model' (TAM). The factors investigated alongside TAM variables were teachers' data like; age, sex, and residence type. TAM items that were correlated in this study included; self-esteem, stress and anxiousness, ease of utilization, behavioural intention, attitude towards AI usage, and expected benefits. The population of this study comprised all science teachers (170) in the Calabar Education Zone of Cross River State, Nigeria. The sample was made up of 79 science teachers comprising (58.22%) 46 females and (41.77%) 33 males. The descriptive and analytical research design was used in this study. A questionnaire named ' Approval of Artificial Intelligence: The Teachers' Eye' Questionnaire (AAITEQ) was used for the study. This study raised 3 research questions. The reliability for AAITEQ was from 0.72 to 0.81 using Cronbach's alpha. Findings indicated that the approval for the utilization of AI was high with an overall mean score of 3.00. The highest predicting value for behaviour intent using TAM variables was the ease of usage r = .789. Science teachers' sex (t, 77 = 1.988; p = .060, ( p ˃ .05), age F (2, 76) = .547; p = .581 ( p ˃ .05) and teachers' residence location (t, .77 = .533; p = − .062 ( p ˃ .05) did not influence the behaviour of science teachers' intention of the utilization of AI. It was recommended that both in-service and pre-service teachers be trained on the utilization of AI.\",\"PeriodicalId\":21774,\"journal\":{\"name\":\"Smart Learning Environments\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":6.7000,\"publicationDate\":\"2023-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Smart Learning Environments\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1186/s40561-023-00261-x\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"EDUCATION & EDUCATIONAL RESEARCH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Smart Learning Environments","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/s40561-023-00261-x","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
Adoption of artificial intelligence in science teaching: From the vantage point of the African science teachers
Abstract This study investigated the factors influencing science teachers' 'Artificial Intelligence' (AI) utilization by using the 'Technology Acceptance Model' (TAM). The factors investigated alongside TAM variables were teachers' data like; age, sex, and residence type. TAM items that were correlated in this study included; self-esteem, stress and anxiousness, ease of utilization, behavioural intention, attitude towards AI usage, and expected benefits. The population of this study comprised all science teachers (170) in the Calabar Education Zone of Cross River State, Nigeria. The sample was made up of 79 science teachers comprising (58.22%) 46 females and (41.77%) 33 males. The descriptive and analytical research design was used in this study. A questionnaire named ' Approval of Artificial Intelligence: The Teachers' Eye' Questionnaire (AAITEQ) was used for the study. This study raised 3 research questions. The reliability for AAITEQ was from 0.72 to 0.81 using Cronbach's alpha. Findings indicated that the approval for the utilization of AI was high with an overall mean score of 3.00. The highest predicting value for behaviour intent using TAM variables was the ease of usage r = .789. Science teachers' sex (t, 77 = 1.988; p = .060, ( p ˃ .05), age F (2, 76) = .547; p = .581 ( p ˃ .05) and teachers' residence location (t, .77 = .533; p = − .062 ( p ˃ .05) did not influence the behaviour of science teachers' intention of the utilization of AI. It was recommended that both in-service and pre-service teachers be trained on the utilization of AI.