Evidence map›Paper›PMID 40477758›Full record

ArticleSmart learning environments2021

Teachers' adoption of an open and interactive e-book for teaching K-12 students Artificial Intelligence: a mixed methods inquiry.

Xiangling Zhang, Ahmed Tlili, Keith Shubeck, Xiangen Hu, Ronghuai Huang, Lixin Zhu

Abstract read
In one paragraph

Article in Smart learning environments, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Xiangling ZhangBeijing Institute of Education, Beijing, China.
Ahmed TliliSmart Learning Institute of Beijing Normal University, Beijing, China.ORCID 0000-0003-1449-7751
Keith ShubeckDepartment of Psychology, The University of Memphis, Memphis, USA.
Xiangen HuDepartment of Psychology, The University of Memphis, Memphis, USA.
Ronghuai HuangSmart Learning Institute of Beijing Normal University, Beijing, China.
Lixin ZhuSmart Learning Institute of Beijing Normal University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the rapid development of information technology, e-books have become convenient for students to improve their learning performance, especially when learning complicated concepts. However, research showed that acceptance of e-books by teachers is fragmented, due to several factors including the e-book design. Therefore, this study combined the potential positive impacts of openness and interaction on learning to design an open and interactive e-book for teaching K-12 students AI. It then applied a mixed method to investigate the factors that affect teachers' acceptance of this open and interactive e-book based on the technology acceptance model (TAM) and interviews. The obtained results showed that teachers' intention to continue using this e-book is significantly influenced by their perceived usefulness and attitude towards this e-book. Additionally, both the interactive and openness features were very helpful for teachers in using this e-book in their teaching plans. However, some of them raised several concerns like the interactive coding platform should be personalized based on students' age. The findings of this study could help different stakeholders (e.g., instructional designers, teachers, policymakers) in facilitating the design and adoption of open and interactive e-books.

Indexed as

Artificial intelligence (AI)e-booksInteractiveOpen educational practices (OEP)Open educational resources (OER)Technology acceptance model (TAM)

Identifiers

PMID40477758
PMCPMC8665326

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.