Testing the effect of information and communication technologies (ICT) integration on nursing students’ motivation: A quasi-experimental research

Abstract

BACKGROUND:

The use of digital technology in healthcare education has become increasingly essential, offering various tools and methods for both classroom and clinical settings. One significant area of interest is the impact of technology on student motivation, which is crucial for academic success across all age groups. This study aims to assess the effect of technology use on nursing students’ motivation, focusing on how educators integrate technology.

MATERIALS AND METHODS:

This quasi-experimental study was conducted at a single nursing education institution and involved 61 sec-semester nursing students. The study utilized a questionnaire comprising socio-demographic data and the Situational Motivation Scale (SMS). The students were divided into two groups: one group experienced passive use of Information and Communication Technologies (ICT), while the other group experienced active use of ICT. Data was collected before the intervention and after the intervention.

RESULTS:

Analyzing the pre- and post-test results for both groups, the experimental group demonstrated significantly higher scores in intrinsic motivation (P = 0.04) and external regulation (P = 0.02). Conversely, the control group experienced a decrease in the motivational scores. Moreover, the experimental group’s Self-Determination index average was higher.

CONCLUSION:

This study underscores the importance of integrating technology in a student-centered approach to enhance nursing students’ motivation. Policymakers and nursing managers should consider these findings when designing educational strategies, emphasizing student-centered approaches and active technology use to enhance motivation and improve learning outcomes in nursing education. Future research could explore longer interventions and additional motivational measures to further understand the impact of technology on student motivation.

Introduction

In the academic context, especially in the field of healthcare, the use of digital technology has become an integral part of health professionals’ education.[1,2] Its numerous benefits have been identified, with a range of tools that can be utilized in both classroom and clinical settings in various forms (software and hardware) and through diverse teaching methods.[3,4,5]

One benefit attributed to technology is its effects on student motivation. The question of fostering motivation for academic success is not only pertinent to the youth in schools but extends to adults seeking to enhance their skills throughout their lives.[6]

Deci and Ryan (1985) introduced the self-determination theory (SDT), a significant motivational framework widely applied today. This theory posits that behavior can be categorized into intrinsic, extrinsic, or a motivated. Intrinsic motivation denotes engaging in an activity for pure enjoyment and satisfaction. Conversely, extrinsic motivation is driven by external factors, where participation is prompted by outside rewards. Amotivation (AM) signifies a lack of intention in undertaking an activity, reflecting a disinterest or disregard for its value or outcome.[7] This theoretical perspective has garnered substantial attention in recent research, particularly in the realm of education.[8,9]

One prevalent approach of studying technology integration in classroom involves categorizing digital learning activities based on the Interactive Constructive Active Passive (ICAP) framework developed by Chi and Wylie (2014). This framework outlines four distinct engagement levels achievable by incorporating technology in education.[10,11]

In a similar vein, Chiara Antonietti and colleagues[11] have developed a tool to measure how technology is integrated into educational tasks. They emphasize that the impact of technology on learning outcomes depends on how it is used and the specific activities it supports. They distinguish between passive learning, where learners absorb content without overtly engaging with it (like watching a video), and active learning, where learners manipulate the material (such as controlling video playback).

Upon reviewing recent literature on the topic, findings indicate a positive impact of technology on student motivation. Dhanda[12] described how students are motivated by technology, both intrinsically and extrinsically, for educational purposes. The study concluded that students’ preference for using technology is influenced by factors such as satisfaction, sense of accomplishment, and the immediate feedback it provides, which enhance their motivation to use it. Similarly, students feel motivated when incorporating technology into face-to-face teaching.[13] Additionally, Lozano-Lozano and colleagues,[14] in an experimental design, discovered that the blended learning approach resulted in notable enhancements in motivation, mood, and satisfaction when compared to conventional teaching methods.

In another study that assessed nursing student motivation in a flipped classroom setting, results indicated a positive improvement in motivation scores for all students (n = 20) compared to those in the traditional teaching method.[15]

While the promise of improved student motivation with technology integrated teaching engagement looms large, concerns persist about the effective use to attain good academic results. Thus, we need to carefully study how technology is used in education to understand its real impact on the most critical stakeholders—the students. Moreover, there is a notable shortage of published works that specifically explore the intersection of technology and student motivation through the lens of SDT, particularly within the field of health profession education. Therefore, it is crucial to critically assess the various strategies for incorporating technology into the classroom. Further, establishing and enhancing leadership in digital learning within the field of nursing is essential for advancing nursing education and practice, ultimately leading to better outcomes for students, educators, and patients alike.[16,17]

In this perspective, the primary objective of this research paper is to assess the effect of technology use on nursing students’ motivation, with a specific focus on how educators incorporate technology. By undertaking this research, we aim to fill the current gap in empirical data and provide valuable insights to educational stakeholders regarding the best strategies for utilizing technology to increase student motivation. Uncovering the dynamics between technology use and student motivation is pivotal to designing evidence-based strategies that optimize the benefits of technology while mitigating its potential drawbacks.

Materials and Methods

Study design and setting

This research employs a quasi-experimental design to investigate the effect of teachers’ use of Information and Communication Technologies (ICT) on the motivation of nursing students. Participants in this study were from a single nursing education institution in the south east of Morocco. The research was carried out between February and April 2023.

Study participants and sampling

The study enrolled nursing students in their second semester, including all first-year cohort. It involved a total of 61 participants, divided into two groups: a control group and an experimental group [Table 1].

Table 1.

Teachers and student’s role in the learning process at the time of digital tool integration

		Experimental group		Control group
Teacher		Teacher takes on a more facilitative role by actively encouraging students to engage with ICT tools through student-centered digital learning activities.		In this group, the teacher uses ICT tools in a traditional manner, adopting one-way communication through presentations. Their main role is to deliver content.
Students		Students actively participate in the learning process by using technology to develop educational materials. Students use technology to create PowerPoint presentations and produce video capsules.		Students are passive recipients of technology-mediated teaching. They consume the provided educational content, but do not actively interact with technology to create their own products or participate actively in the learning process at the time of digital tool integration.

ICT: Information and Communication Technologies

Data collection tool and technique

Data collection in this study is based on a questionnaire comprising two main sections: socio-demographic data (e.g. age and sex) and student motivation via the Situational Motivation Scale (SMS).

Student motivation via SMS

The scale is a validated questionnaire developed by Guay et al.,[7] operationalizing elements of the SDT continuum developed by Deci and Ryan. The Situational Motivation Scale is the self-assessment questionnaire designed to evaluate individuals’ motivation in a specific context, such as the classroom or educational environment. It includes items that measure different types of motivation and non-motivation: Intrinsic Motivation, Identified Regulation, External Regulation, and AV.

Each of the four subtypes of motivation was measured using seven-point Likert scales (ranging from “Strongly Disagree” to “Strongly Agree”), with four questions for each motivation subscale.[7,18]

Data collection procedure

Student are divided into two groups: The Passive Use of ICT Group (PUIG), in which technology is used passively, primarily through digital presentations. In contrast, the second group, termed the Active Use of ICT Group (AUIG), involves a more active technology use by students [Table 1].

In this study, the motivation measurement scale was administered to nursing students at two different points in time: before the intervention (pre-intervention) and after the intervention (post-intervention). This will enable researchers to compare changes in motivation levels between the PUIG and the AUIG following the educational intervention.

The intervention takes place over 8-week period and targets first-year students. It consists of providing a “nursing philosophy” course, allowing students to delve into diverse nursing philosophies and theories. The course aims to impart essential principles, values, and approaches that guide nursing practice and caregiving.

In both the PUIG and the AUIG, the teacher follows the similar pedagogical approach. This methodological uniformity helps control confounding variables and establish the causal link between technology use and students’ motivation.

Data analysis

Initially, the collected data was analyzed using descriptive statistics to provide data characterization. Mean and standard deviation were calculated for continuous data, while percentages were used for categorical data. Comparisons between different values were analyzed using the paired t-test and the Mann-Whitney test. The statistical software SPSS version “21.0” was used for data analysis. The significance level was set at P < 0.05.

Ethical considerations

This study prioritizes the rights and well-being of participants by implementing several ethical measures. Approval was obtained from the Ethics Committee of the university where the research team was affiliated (FLSH.CE.12.2023). Prior to participating, all students were briefed on the research objectives and their right to withdraw. Anonymity and confidentiality were ensured, with data anonymized during analysis.

Results

The sample characteristics are presented in Table 2.[19] According to this data, most students in both groups own a computer. In terms of gender, the majority in both groups are female. Additionally, most students in both groups come from rural backgrounds and express a favorable attitude toward academic use of ICT. The average age in the experimental group is 19.15 (SD = 1.46), while in the control group, it is 19.88 (SD = 3.75) [Table 2].

Table 2.

Characteristics of the participants

				Control group		Experimental group
Possession of a computer		Yes		20 (58.8%)		15 (55.6%)
		No		14 (41.2%)		12 (44.4%)
Gender		F		26 (76.5) %		22 (81.5%)
		M		8 (23.5%)		51 (8.5%)
Origin		Urban		15 (44.1%)		11 (40.7%)
		Rural		19 (55.9%)		16 (59.3%)
Attitude towards the pedagogical use of ICT		For		27 (79.4%)		25 (92.6%)
		Against		7 (20.6%)		2 (7.4%)
Age M (SD)				19.88 (3.75)		19.15 (1.46)

ICT: Information and Communication Technologies

The effect of technology use on nursing students’ motivation

Before conducting the post-test analyses, it was examined whether there was a significant difference in motivation between the groups based on their pre-test scores.

For intrinsic motivation, identified regulation, external regulation and AM, the means are relatively close in both groups, with high P values (0.41, 0.08, 0.33, 0.91, respectively) indicating that there is no significant difference between the two groups on these aspects of motivation at pretest [Table 3].

Table 3.

Pre-tests findings for the experiment and control group

		Control group				Experimental group				U		P
		M		SD		M		SD
Intrinsic motivation		20.15		5.88		18.04		7.17		402		0.41
Identified regulation		21.09		5.55		19.44		7.19		508.5		0.08
										t		P
External regulation		15.44		4.98		14.18		5.0		0.98		0.33
Amotivation		13.70		5.72		13.55		5.14		0.10		0.92

As for post-tests, Table 4 presents the results of the independent groups t-test carried out to examine the difference between the post-test motivation scores of students in the experimental and control groups. The results indicate that there is a slight difference between the post-test scores of students in the experimental and control groups, in favor of the experimental group in external regulation and in favor of the control group in AM. The means of the intrinsic motivation and identified regulation scores for the experimental group are higher than those of the control group. However, these differences were not statistically significant.

Table 4.

Post-tests comparison of motivational scores between the two groups

		Control group				Experimental group				t		P
		M		SD		M		SD
Intrinsic motivation		18.74		6.99		21.48		6.94		580.5		0.07
Identified regulation		19.97		6.78		20.59		6.81		490.5		0.64
External regulation		15.18		6.85		16.44		5.19		0.8		0.43
Amotivation		12.79		5.72		12.70		5.28		0.06		0.95

By comparing a group’s pre- and post-test scores, we can determine whether there has been a significant change in learner motivation. By comparing participants’ pre- and post-intervention scores, we can examine growth or changes in motivation over time under the influence of the intervention of using technology in a different way between the two groups, and determine whether these changes are statistically significant.

Regarding intrinsic motivation, an improvement in scores was observed among students in the experimental group. However, a regression in scores was noted among students in the control group. The difference observed between the two scores for students in the experimental group is statistically significant, with a P value of 0.04 [Table 5].

Table 5.

Comparison of pre-test/post-test scores of for the two groups for autonomous motivation

		Intrinsic motivation								Identified regulation
		Pre-test M (SD)		Post-test M (SD)		U		P		Pre-test M (SD)		Post-test M (SD)		U		P
Experimental group		18.04		21.48		232		0.04		19.44		20.51		162		0.25
		(7.17)		(6.96)						(7.1)		(6.8)
Control group		20.14		18.73		141		0.38		21.09		19.97		168		0.43
		(5.87)		(6.99)						(5.55)		(6.78)

SD: Standard deviation

In addition, the experimental group showed an increase in identified regulation scores from pre-test to post-test, while the control group’s scores decreased. However, the difference in identified regulation scores between the two groups was not statistically significant.

As for the external regulation, the experimental group demonstrated a significant improvement rising from a mean of 14.19 at pre-test to 16.44 at post-test, with a statistically significant difference between pre-test and post-test (P = 0.02). The control group showed a slight decrease in scores, which was not statistically significant.

When it comes to amotivation, pre- and post-test scores analysis of students in both groups reveals that there was a slight decrease in the amotivation dimension among students in both groups. However, this decrease did not reach a statistically significant level [Table 6].

Table 6.

Comparison of pretest-post-test scores of for the two groups for external regulation and amotivation

		External regulation								Amotivation
		Pre-test M (SD)		Post-test M (SD)		t		P		Pre-test M (SD)		Post-test M (SD)		t		P
Group of control		15.44 (4.98)		15.18 (6.85)		0.28		0.78		13.7 (5.72)		12.79 (5.72)		0.96		0.34
Experimental group		14.18 (5)		16.44 (5.2)		2.44		0.02		13.55 (5.14)		12.7 (5.28)		0.65		0.56

Discussion

The main aim of this study was to assess the effect of technology use on nursing students’ motivation, focusing specifically on how it is implemented. What makes this study special is that it highlights the difference that can exist between two ways of integrating technology into student learning.

According to the results obtained, it was found that the experimental group, where content was taught based on student-centered technology integration, displayed higher motivation compared to the control group.

About the analysis of post-test scores of two groups, the results revealed a slight increase in favor of the experimental group, however, these differences were not statistically significant. Nevertheless, it is important to consider that student motivation is a complex and multifactorial concept, and that a single pedagogical intervention, in a limited period, may not be sufficient to bring about significant changes. Future studies could explore longer interventions, additional teaching strategies and a variety of motivational measures to better understand how technology and pedagogical approaches can influence student motivation more thoroughly.

The analysis of the pre- and post-test results for both groups, focusing on the characteristics of student motivation within the framework of SDT, revealed a significant difference in favor of the experimental group regarding intrinsic motivation (P = 0.04) and external regulation (P = 0.02). In contrast, a regression in scores was observed among students in the control group. These results indicate that integrating technology into a student-centered approach (intervention with the experimental group) can improve student motivation. In contrast, passive integration of technology can have a demotivating effect on students.

In the experimental group, students showed a greater inclination to be intrinsically motivated, suggesting that they were more interested and engaged in their learning as a result of the student-centered approach and active use of technology.[19,20] However, external regulation of motivation concerns the influence of external factors such as rewards or external pressures on student motivation. This means that students in the experimental group were better able to regulate their motivation in response to external incentives or encouragement.

According to Ryan and Deci’s SDT (Ryan and Deci[18]), people are motivated by three inherent psychological needs: autonomy, relatedness, and competence. The higher score of the experimental group for intrinsic motivation indicates that students generally feel a significant degree of autonomy and self-control when using digital learning tools. This supports SDT’s focus on autonomy as a key psychological need. In a related study, Naciri et al.[15] found that involvement in online learning activities is a predictor of intrinsic motivation. In another study that examined the motivation of nursing students in a flipped classroom setting, the results showed a positive increase in motivation scores for all students (n = 20) compared to those using traditional teaching methods. This increase in intrinsic motivation was attributed to the pedagogical approach of the flipped classroom. These results suggest that technology alone is not enough to create effective learning experiences; it must be combined with a suitable pedagogical approach.[21]

In the same vein, Abou El-Seoud et al.[22] emphasizes that incorporating interactive e-learning elements, like the Moodle platform, enhances motivation among undergraduate students in Egyptian universities. Supporting students in leveraging ICT for learning is crucial, and teachers play a significant role in this, as highlighted in the study. Our results are also consistent with prior research, who demonstrated that the use of an e-learning approach, together with the active use of interactive features improves student motivation.[23,24]

The results underline the importance of thoughtfully integrating technology to promote intrinsic student motivation. Placing the student at the center of pedagogical practice is strongly recommended.[4,25] Teachers should consider student-centered pedagogical approaches, where technology is used as a means to facilitate their active engagement.

Limitations and recommendations

While this study is one of the fewest adopting an experimental design to shed light on the influence of technology integration on nursing students’ motivation, it is important to acknowledge certain limitations. Firstly, the research may be subject to contextual constraints, as the findings may be specific to the educational environment and technological resources available. Additionally, the study’s scope may not encompass all possible variables that could impact student motivation, such as individual learning styles or external factors beyond technology use. Moreover, the study’s design may rely on self-reported data, which could introduce potential biases or inaccuracies. Finally, the research may not capture long-term effects, as motivation and technology integration dynamics may evolve over time. Recognizing these limitations provides a foundation for future studies to build upon and refine our understanding of this complex relationship.

To enhance nursing students’ motivation through technology integration, it is recommended to adopt student-centered pedagogical approaches that prioritize active participation and engagement. Providing students with autonomy and self-governance in their learning process, aligned with SDT, can also boost motivation. Professional development programs, including workshops and mentorship opportunities, should be provided to educators to enhance their skills in incorporating ICT and fostering leadership in digital teaching.[17,26,27,28,29] Additionally, establishing peer learning communities and mentorship programs can create supportive environments where educators can share best practices and receive guidance from experienced peers. Furthermore, educators should be encouraged to engage in research on digital teaching practices to contribute to the advancement of knowledge in the field.

Conclusion

This research contributes to educational technology by exploring how integrating technology can enhance student motivation. The study found that student-centered technology integration led to higher motivational scores in the experimental group, indicating a more engaging learning environment. The findings highlight the importance of aligning technology and pedagogy for a stimulating learning experience.

For health policymakers and nursing managers, these findings suggest the importance of investing in technology and providing educators with the necessary training and resources to effectively integrate technology into their teaching practices. Supporting curriculum development that integrates technology in meaningful ways can enhance the overall learning experience. Moreover, policymakers and managers should create a supportive environment for innovative practices that incorporate technology, facilitate collaboration among educators, and encourage research on the impact of technology in nursing education.

This research provides guidance to educators on using technology to motivate students, particularly within the realm of health professional education. However, additional research is necessary to further investigate this inquiry, utilizing various methodological approaches to explore the potential effects of technology on student motivation and academic performance in greater detail.

Author’s contribution

Concept: DAA and FC. Design: HK and AR. Literature search: DAA. Data analysis: DAA. Statistical analysis: DAA. Manuscript preparation: DAA and HK. Manuscript editing and manuscript review: All authors. Guarantor: DAA.

All authors have read and approved the final manuscript. The requirements for authorship have been met, and each author believes that the manuscript represents honest work.

Consent to participate

All participants were briefed on the study’s purpose and informed that participation was voluntary. Verbal informed consent was obtained from participants before data collection, ensuring confidentiality.

Conflict of interests

The authors declare no conflict of interest

Data availability statement

The data supporting the findings of this study can be obtained from the corresponding author upon request.

Funding Statement

This research was funded by “Le Centre National de Recherche Scientifique et Technique, Maroc: Cov/2020/28) and by the “Lifelong Learning Observatory (UNESCO).