研究生: |
洪瑞成 Hong, Rui-Cheng |
---|---|
論文名稱: |
建構學習輔助科技需求考量因素及工具之研究-以閱讀學習輔助科技為例 Research on constructing the causal model for considering the needs of assistive technology for learning: the consideration tools for reading assistive technology |
指導教授: |
林幸台
Lin, Hsin-Tai |
學位類別: |
博士 Doctor |
系所名稱: |
特殊教育學系 Department of Special Education |
論文出版年: | 2020 |
畢業學年度: | 108 |
語文別: | 中文 |
論文頁數: | 138 |
中文關鍵詞: | 學習輔助科技 、閱讀學習輔助科技需求考量工具 、閱讀困難 、PLS-SEM |
英文關鍵詞: | learning assistive technology, tool for reading assistive technology needs consideration, reading difficulties, PLS-SEM |
DOI URL: | http://doi.org/10.6345/NTNU202001154 |
論文種類: | 學術論文 |
相關次數: | 點閱:301 下載:59 |
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本研究旨在建構學習輔助科技需求考量之因素及結構模式,並以閱讀學習輔助科技為例發展需求考量工具。依據研究目的本研究分為兩個子研究,研究一為探討學習輔助科技需求考量因素與結構模式,以67位美國輔助科技專業人員以及60位我國特殊教育人員為對象,了解研究者由輔助科技模式提取歸納出的能力、表現、動機、學習輔助科技知識經驗四項因素,是否會影響輔助科技專業及特殊教育人員對學習輔助科技需求覺知。再依輔助科技模式理論之關係,將四項因素作為潛在因素建構學習輔助科技需求考量結構模式,利用PLS-SEM分析測量模式及因果路徑模式之適配度,依分析驗證結果據以修正結構模式,同時使用PLS的多族群分析(MGA)技術,分析美國與我國資料樣本投入該結構模式時是否有差異,以確認該結構模式於我國教育現場使用之適切性。研究二則利用研究一所建構之因素與結構模式,由研究者與兩位專家共同發展閱讀學習輔助科技需求考量工具,並邀請10位分布於各縣市不分類資源班教師,以其服務的3位閱讀困難學生為對象使用工具進行閱讀學習輔助科技需求之考量,蒐集30位學生的閱讀學習輔助科技需求評估結果,並依分析結果訪談10位教師使用工具之感受。綜整研究一及研究二之結果,提出研究結論如下:
一、 學習能力、學習表現、學習動機、學習輔助科技知識經驗四項因素會影響學習輔助科技需求之考量。以四項因素進行學習輔助科技需求判定時,美國輔助科技專業人員與我國特殊教育專業人員在不同因素下也有差異。
二、 以學習能力、學習表現、學習動機、學習輔助科技知識經驗四項因素所建構的結構模式,在測量模式與因果路徑模式皆通過PLS-SEM之驗證標準,因素結構具信、效度且與理論相符。以美國輔助科技專業人員為資料樣本所建構的學習輔助科技結構模式與我國特殊教育專業人員在結構模式之多族群分析並無顯著差異。
三、 閱讀學習輔助科技需求考量工具為一含括需求考量評估、需求考量建議與資源提供之三步驟整合性工具,作為需求考量評估步驟之閱讀學習輔助科技需求考量評估表具備可接受的信、效度。使用之教師對該工具功能性與實用性之感受皆給予肯定且正向的回饋。
依據以上研究結果,研究者提出學習輔助科技考量因素及工具在實務應用與未來研究之建議。
The purpose of this research is to construct the factors and causal models for the consideration of learning assistive technology needs and to develop the tool for teacher to consider the needs of reading assistive technology. This research is divided into two sub-studies. The first study is to explore the factors and structural models of learning assistive technology needs. Four factors: capability, performance, motivation, and assistive technology knowledge and experience were retrieved from 15 AT conceptual models. 67 assistive technology professionals and specialists in U.S and 60 special education professionals in Taiwan were invited to participate in the survey to test whether the four factor will affect the recognition of the learning assistive technology needs. Based on the theory of AT model, four factors were used as potential factors to construct the casual model of learning assistive technology needs consideration. Researcher used the PLS-SEM to analyze the fitness of measurement model and casual model, and based on the result to fix the model. When the model fits the standard of PLS-SEM, PLS MGA was used to check the difference between the group of data from U.S and Taiwan to ensure the model can be also used in Taiwan. In the second study, two special education teachers who were proficient in assistive technology and learning disability were invited by researcher to develop the tool for the consideration of reading assistive technology needs by using the factors and model constructed in first study. There were 10 special education teacher who served in resource classroom in different county in Taiwan participated the study, each of them was requested to evaluate 3 students who were qualified with learning disabilities and reading difficulties by using the tool for consideration of reading assistive technology needs. 30 student’s data of reading assistive technology needs were collected and analyzed. With the data, researcher conducted the Semi-Structured Interviews to the 10 teachers to know the feelings and feedback about the tool they used to considerate the reading assistive technology needs for the students. The results of Study 1 and Study 2 were hereby presented as follows:
1. The four factors: capability, performance, motivation, and learning assistive technology knowledge and experience will affect the consideration of learning assistive technology needs. There were differences between assistive technology professionals and specialists in U.S and special education professionals in Taiwan under different factors when recognizing the learning assistive technology needs.
2. The model constructed with four factors: capability, performance, motivation, and learning assistive technology knowledge and experience. Both the measurement model and causal model fitted PLS-SEM standard, and the outer model had acceptable reliability and validity, and the inner model was consistent with theory. There is no significant difference by using PLS Multi-Group Analysis to analyze the respondents of special education professionals in our country and assistive technology professionals and specialists in U.S as data samples in the model.
3. Assistive Technology Needs Consideration Tool for Reading is a three-step integrated tool that included needs evaluation, advice of needs consideration, and resource index. The Reading Assistive Technology Needs Evaluation Form, one of the tool for considering the reading assistive technology needs, had acceptable reliability and validity. 10 teachers all gave the tool a positive review and felt the tool produced a useful suggestion when considering the reading assistive technology needs and plan the special education service for the students.
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