Primary school teachers’ attitudes toward technology use and stimulating higher-order thinking in students: a review of the literature

Figures & data

Table 1. Models of factors impacting technology use.

Technology Acceptance Model (TAM 1)	Davis (1989)
TAM 2	Venkatesh and Davis (2000)
TAM 3	Venkatesh and Bala (2008)
Unified Theory of Acceptance and Use of Technology (UTAUT)	Venkatesh et al. (2003)
Integrative Model of Behavior Prediction (IMBP)	Kreijns et al. (2013)
Will, Skill, Tool and Pedagogy model (WSTP)	Knezek and Christensen (2016)
Technological, Pedagogical, and Content Knowledge framework (TPACK)	Mishra and Koehler (2006)

Table 2. Types of documents in the body of included studies.

Type of document	Number of studies
Scientific journal article	73
Conference paper	4
Research report	1
Total	78

Table 3. Number of studies reporting on the identified attitudinal factors.

Factor	Definition	Number of studies	Types of data*
			Qualitative	Quantitative	Mixed
Cognitivedimension
Perceived usefulness	Teachers’ beliefs about the usefulness of technology for improving and/or enriching their teaching and the learning of their students	47	18	20	9
Perceived ease of use	Teachers’ beliefs about the ease or difficulty of using technology in their teaching	9	1	4	4
Perceived relevance	Teachers’ beliefs about the importance of using technology in their teaching in order to prepare students for later life	8	5	2	1
Perceived effect on student motivation	Teachers’ beliefs that using technology in teaching motivates students to learn and engages students in learning	19	10	7	2
Affective dimension
Anxiety	Negative feelings such as anxiety or fear when using technology	6	1	1	4
Enjoyment	Positive feelings such as enjoyment or enthusiasm when using technology	7	2	2	3
Perceived behavioral control dimension
Self-efficacy	Teachers’ self-perceived capability to use technology in their teaching	35	9	17	9
Context dependency	Teachers’ perceptions that external factors, (i.e., availability of resources, support, available time) are a prerequisite for them to be able to use technology	12	4	5	3
Social norms dimension
Subjective norms	Teachers’ perceptions as to whether other people who are important to that teacher think it is good or bad to use technology in teaching	19	3	11	5

* In some of the mixed-method studies, only the qualitative data were used if the items from the questionnaire were not described.

Figure 1. Studies investigating the influence of the attitudinal factors on teachers’ (intended) use of technology in teaching.

Notes:

1. Numbers refer to the number of studies investigating the influence on teachers’ intended/actual technology use.

2. Positive (+), negative (−), or varied (±) influence on teachers’ intended/actual technology use.

Table 4. Types of documents in the body of included studies.

Type of document	Number of studies
Scientific journal article	16
Research report	1
Conference paper	1
Total	18

Table 5. Number of studies reporting on the identified attitudinal factors.

		Number of studies	Types of data
Factor	Definition		Qualitative	Quantitative	Mixed
Cognitive dimension
Perceived relevance	Teachers’ belief about the importance of stimulating higher-order thinking in students in order to help them develop the necessary skills they will need in later life	9	7	0	2
Perceived student ability	Teachers’ beliefs about the capacity of students to engage in higher-order thinking	9	7	1	1
Affective dimension		–	–	–	–
Perceived control dimension
Self-efficacy	Teachers’ self-perceived capability to stimulate higher-order thinking in students	7	3	4	0
Context dependency	Teachers’ perception that external factors are a prerequisite for being able to stimulate higher-order thinking in students	10	6	2	2
Social norm dimension		–	–	–	–

Figure 2. Studies exploring the influence of the attitudinal factors on teachers’ intention/behavior aimed at stimulating higher-order thinking in students. Notes: 1. No studies reported on the influence of the identified factors on teachers’ intention/behavior aimed at stimulating higher-order thinking in students.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008

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Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273–315. https://doi.org/10.1111/j.1540-5915.2008.00192.x

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Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. doi:.2307/30036540

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Kreijns, K., Vermeulen, M., Kirschner, P. A., van Buuren, H., & van Acker, F. (2013). Adopting the integrative model of behaviour prediction to explain teachers’ willingness to use ICT: A perspective for research on teachers’ ICT usage in pedagogical practices. Technology, Pedagogy and Education, 22(1), 55–71. https://doi.org/10.1080/1475939X.2012.754371

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Knezek, G., & Christensen, R. (2016). Extending the will, skill, tool model of technology integration: Adding pedagogy as a new model construct. Journal of Computing in Higher Education, 28(3), 307–325. https://doi.org/10.1007/s12528-016-9120-2

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Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017–1054. https://doi.org/10.1111/j.1467-9620.2006.00684.x

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