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Research on Teaching Quality Evaluation of Interactive Mobile AI Smart Classrooms Based on AHP.

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Title: Research on Teaching Quality Evaluation of Interactive Mobile AI Smart Classrooms Based on AHP.
Authors: Liu, Quan1, Guan, Jingjing1 18971083933@163.com, Efendiev, Rakib2
Source: International Journal of Interactive Mobile Technologies. 2026, Vol. 20 Issue 11, p126-137. 12p.
Subjects: Analytic hierarchy process, Evaluation methodology, Educational objectives, Effective teaching, Student-centered learning, Educational technology, Experiential learning
Abstract: The interactive mobile artificial intelligence (AI) smart classroom is a new teaching model that deeply integrates mobile terminals, AI, and classroom instruction. However, current teaching quality evaluations face challenges such as high subjectivity and vague indicators. To address these issues, this paper selects five evaluation factors: teaching objectives, interactive teaching processes, AI application, learning experience, and teaching effectiveness. The analytic hierarchy process (AHP) is first utilized to determine the weight of each indicator, followed by the Fuzzy comprehensive evaluation (FCE) method for integrated assessment. This study selects three representative smart teaching courses offered in universities as empirical samples for analysis. The results indicate that Research Methods in Educational Technology scored 86.77, Python Programming scored 86.29, and Design and Development of Smart Courses scored 90.86. Overall, the performance ranges from "Good" to "Excellent." These findings provide a quantitative basis for teachers to optimize instruction and for institutions to improve management levels. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Interactive Mobile Technologies is the property of International Journal of Interactive Mobile Technologies and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: Research on Teaching Quality Evaluation of Interactive Mobile AI Smart Classrooms Based on AHP.
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  Data: <searchLink fieldCode="AR" term="%22Liu%2C+Quan%22">Liu, Quan</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Guan%2C+Jingjing%22">Guan, Jingjing</searchLink><relatesTo>1</relatesTo><i> 18971083933@163.com</i><br /><searchLink fieldCode="AR" term="%22Efendiev%2C+Rakib%22">Efendiev, Rakib</searchLink><relatesTo>2</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Interactive+Mobile+Technologies%22">International Journal of Interactive Mobile Technologies</searchLink>. 2026, Vol. 20 Issue 11, p126-137. 12p.
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  Data: <searchLink fieldCode="DE" term="%22Analytic+hierarchy+process%22">Analytic hierarchy process</searchLink><br /><searchLink fieldCode="DE" term="%22Evaluation+methodology%22">Evaluation methodology</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+objectives%22">Educational objectives</searchLink><br /><searchLink fieldCode="DE" term="%22Effective+teaching%22">Effective teaching</searchLink><br /><searchLink fieldCode="DE" term="%22Student-centered+learning%22">Student-centered learning</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+technology%22">Educational technology</searchLink><br /><searchLink fieldCode="DE" term="%22Experiential+learning%22">Experiential learning</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The interactive mobile artificial intelligence (AI) smart classroom is a new teaching model that deeply integrates mobile terminals, AI, and classroom instruction. However, current teaching quality evaluations face challenges such as high subjectivity and vague indicators. To address these issues, this paper selects five evaluation factors: teaching objectives, interactive teaching processes, AI application, learning experience, and teaching effectiveness. The analytic hierarchy process (AHP) is first utilized to determine the weight of each indicator, followed by the Fuzzy comprehensive evaluation (FCE) method for integrated assessment. This study selects three representative smart teaching courses offered in universities as empirical samples for analysis. The results indicate that Research Methods in Educational Technology scored 86.77, Python Programming scored 86.29, and Design and Development of Smart Courses scored 90.86. Overall, the performance ranges from "Good" to "Excellent." These findings provide a quantitative basis for teachers to optimize instruction and for institutions to improve management levels. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of International Journal of Interactive Mobile Technologies is the property of International Journal of Interactive Mobile Technologies and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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        Value: 10.3991/ijim.v20i11.61825
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      – Code: eng
        Text: English
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        StartPage: 126
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        Type: general
      – SubjectFull: Evaluation methodology
        Type: general
      – SubjectFull: Educational objectives
        Type: general
      – SubjectFull: Effective teaching
        Type: general
      – SubjectFull: Student-centered learning
        Type: general
      – SubjectFull: Educational technology
        Type: general
      – SubjectFull: Experiential learning
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      – TitleFull: Research on Teaching Quality Evaluation of Interactive Mobile AI Smart Classrooms Based on AHP.
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            NameFull: Liu, Quan
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            NameFull: Guan, Jingjing
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            – D: 01
              M: 06
              Text: 2026
              Type: published
              Y: 2026
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