Learning motivation is an important factor in the teaching learning process in a digital environment. This study aims to examine self-determined motivation levels and associated factors among health professions students in distance learning activities.
A cross-sectional, analytical, quantitative, multicenter study was conducted among health professions students from February 15, 2022, to July 31, 2022. Students’ self-determined motivation was assessed using a self-administered instrument. It consisted of 16 items categorized into four dimensions: intrinsic motivation, external regulation, identified regulation, and amotivation. It was based on 7-point Likert scale, ranging from 1 (strongly disagree) to 7 (strongly agree). Student engagement was examined using 15 items classified into the following subscales: behavioral, emotional, and cognitive engagement. A correlation between student motivation and engagement was performed. Univariate and multivariate logistic regression analyses were used to identify factors associated with students’ self-determined motivation in distance learning activities.
Of 1,121 students invited to the study, 1,061 valid questionnaires were received, giving a response rate of 94.6%; 595 participants (56.1%) were self-determined in distance pedagogical activities. Multiple regression analysis showed that ethnicity (adjusted odds ratio [aOR], 0.25; 95% confidence interval [CI], 0.08–0.73; p=0.012), educational level (aOR, 1.65; 95% CI, 1.16–2.34; p=0.005), distance learning environment (aOR, 1.65; 95% CI, 1.19–2.29; p=0.003), and student engagement: (aOR, 2.9; 95% CI, 2.21–3.80; p<0.001) were the significant factors associated with students’ self-determined motivation in distance learning.
This study predicted some factors influencing students’ self-determined motivation. Health professions teachers need to be encouraged to adopt effective pedagogical practices in order to maintain and develop student motivation.
The paradigm of higher education has undergone a radical change with the succession of several variants of coronavirus. Indeed, a significant increase in the use of information technology and education use was recorded during the crisis and the post-coronavirus disease 2019 (COVID-19) phase. Several tools were developed to create digital environments for teaching and learning in a distance context. Besides, many factors influence the success of the distance learning process. Students learning motivation was identified as a significant component [
A cross-sectional, analytical, quantitative, multicenter study was conducted using a self-administered questionnaire.
This study was carried out across four Higher Institutes of Nursing Professions and Health Techniques (ISPITS) in different regions of the Kingdom of Morocco: Marrakech-Safi, Souss Massa, Guelmim-Oued Noun, and Laâyoune-Sakia El Hamra. ISPITS form health professionals in five fields and several options. Further detail in
The questionnaire used in this study was self-administered. It was first tested among 20 undergraduate students. The instrument is divided into three parts: the first part captures socio-demographic data and students’ experiences of distance learning (13 items), including age, gender, ethnicity, marital status, higher education institute, discipline, educational level, platform/application used, device/gadget used, internet quality, location of distance learning courses, distance learning environment, and number of distance learning courses attended during the study. The second part concerns the students’ motivation in distance learning, and the last part relates to students’ engagement in distance activities. The parts of the questionnaire concerning student motivation and engagement are described as follows:
Student learning motivation in distance learning was examined using the Situational Motivation Scale (SIMS). The SIMS is 16 items validated instrument developed by Guay et al. [
The adapted version of “the engagement scale” was the tool used to assess students’ engagement in distance learning activities. It consisted of 15 items categorized into the following subscales: behavioral engagement, emotional engagement, and cognitive engagement. Each item was scored on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). Internal consistency coefficients were: emotional engagement (α=0.88), cognitive engagement (α=0.75), and behavioral engagement (α=0.63) [
Data management and statistical analysis were performed using SPSS ver. 13.0 (SPSS Inc., Chicago, USA). Categorical variables were presented as frequency, percentages, and mean±standard deviation. Furthermore, we performed the chi-square test to identify differences in the proportions of categorical variables between the two groups (low and high self-determined motivation). Pearson correlation coefficients were calculated to describe the linear association between motivation and student engagement. Correlation coefficients whose magnitude are between 0.7 and 0.9 indicate variables which can be considered highly correlated [
This study was approved by the Ethics Committee for Biomedical Research of Faculty of Medicine and Pharmacy, Mohammed V University, Rabat, Morocco (registration number: 20/22). Consent was obtained from each participant, and confidentiality was assured.
Of 1,121 participants invited to the study, 1,061 students completed the questionnaire, giving an overall response rate of 94.6%. Descriptive statistics show that the participants’ mean age was 20.2±1.3 (
On the other hand, the study’s results showed that 595 participants (56.1%) were self-determined in distance education. Among these students, 416 (69.9%) were female, 574 (96.5%) were from Morocco, and 579 (97.3%) were single. The self-determined students were 1st year undergraduate 312 (52.4%) from Ispits of Laayoune 230 (38.6%), and 194 (32.6%) from Ispits of Marrakech. The generalist nursing students were the most self-determined 317 (53.3%), and 67 (11.3%) were anesthesia-resuscitation nursing students. WhatsApp Messenger was the most used application for self-determined students 324 (54.4%), while 144 (24.2%) attended Google Classroom. More than 2/3 of the self-determined students 411 (69.1%) reported using mobile phones during distance learning, and 351 (59%) mentioned that the internet connection was good. The majority 539 (90.5%) took distance learning courses from their homes, and 258 (43.3%) reported that the distance learning environment was appropriate. Moreover, 200 (33.6%) of the self-determined students completed at least one distance learning course during the study’s questionnaire response. Regarding online student engagement, out of the 623 students who were highly engaged, 424 (68.1%) showed self-determined motivation.
Univariate logistic regression analysis showed that students’ self-determined motivation is potentially associated with: ethnicity (Moroccan: odds ratio [OR], 0.30; 95% confidence interval [CI], 0.11–0.79; p=0.015), distance learning environment (slightly appropriate: OR, 1.959; 95% CI, 1.43–2.69; p<0.001; appropriate: OR, 1.980; 95% CI, 1.48–2.65; p<0.001), and student engagement (high: OR, 3.327; 95% CI, 2.58–4.29; p<0.001). Other variables were not significantly different. Further details are presented in
Variables with a p-value <0.25 in the univariate analysis were considered in a multivariate logistic regression analysis to obtain a predictive model. Indeed, out of the 10 variables that were included in the multivariate analysis, four were included in the final model as factors associated with students’ self-determined motivation: ethnicity (Moroccan: adjusted odds ratio [aOR], 0.25; 95% CI, 0.08–0.73; p=0.012), educational level (1st year bachelor’s degree: aOR, 1.65; 95% CI, 1.16–2.34; p=0.005), distance learning environment (slightly appropriate: aOR, 1.65; 95% CI, 1.16–2.40; p=0.005; appropriate: aOR, 1.65; 95% CI, 1.19–2.29; p=0.003), and student engagement (high: aOR, 2.9; 95% CI, 2.21–3.80; p<0.001) (
The correlation coefficient results show that intrinsic motivation has moderate, positive, and statistically significant correlations with emotional, behavioral, and cognitive engagement (
The current study aims to explore the self-determined motivation levels of health sciences students in a distance learning context, and identify the predictive factors using multivariate logistic regression analysis. The results revealed that health science students showed acceptable levels of self-determined motivation during distance learning courses. This finding is consistent with previous research [
The study has some limitations. First, our results reflect a cross-sectional analysis of student motivation during distance learning. Assessment of motivation through experimentation or longitudinal survey will provide a more in-depth understanding. Second, factors predicting students’ self-determined motivation were not included exhaustively. Third, some students’ responses coincided with the end of the academic year, i.e., the exam period, which may influence their responses.
In conclusion, as a result of these findings, it seems worthwhile to encourage teachers and professors in the health professions to adopt effective pedagogical practices in the context of distance learning in order to maintain and develop student motivation. In other words, although Whatsapp Messenger is effective in distance learning and increases students’ motivation [
none.
The Self-determination Continuum Based on Ryan and Deci [
From Ryan RM et al. Contemp Educ Psychol. 2000;25(1):54–67 [
Fields and Specialties of ISPITS Students Participating in the Study
Study fields | Specialty |
---|---|
Nursing care | Generalist nurse |
Nurse in anesthesia-resuscitation | |
Nurse in emergency and intensive care | |
Community health nurse | |
Midwife | Midwife |
Health techniques | Laboratory technician |
Radiology technician | |
Reeducation and rehabilitation | Ortho-prosthesis |
Kinesitherapy | |
Medical-social assistance | Social worker |
Health sciences education | Master’s degree in nursing and health techniques pedagogy |
ISPITS: Higher Institute of Nursing Professions and Health Techniques.
Participants’ Characteristics, Experiences, and Engagements Based on Their Self-determined Motivation in Distance Learning (N=1,061)
Characteristic | No. (%) | Low self-determined | High self-determined | p-value |
---|---|---|---|---|
Age (yr) | 20.2±1.3 | 0.470 | ||
<21 | 902 (85) | 392 (43.5) | 510 (56.5) | |
>21 | 159 (15) | 74 (46.5) | 85 (53.5) | |
Gender | 0.210 | |||
Female | 725 (68.3) | 309 (42.6) | 416 (57.4) | |
Male | 336 (31.7) | 157 (46.7) | 179 (53.3) | |
Ethnicity | 0.010 | |||
Moroccan | 1,035 (97.5) | 461 (44.5) | 574 (55.5) | |
Other | 26 (2.5) | 5 (19.2) | 21 (80.8) | |
Marital status | 0.153 | |||
Single | 1,025 (96.6) | 446 (43.5) | 579 (56.5) | |
Married | 32 (3) | 19 (59.4) | 13 (40.6) | |
Divorced | 4 (0.4) | 1 (25) | 3 (75) | |
Higher education institute | 0.039 | |||
Ispits Marrakech | 375 (35.3) | 181 (48.3) | 194 (51.7) | |
Ispits Guelmim | 254 (23.9) | 95 (37.4) | 159 (62.6) | |
Ispits Laayoune | 406 (38.3) | 176 (43.3) | 230 (56.7) | |
Ispits Agadir | 26 (2.5) | 14 (53.8) | 12 (46.2) | |
Discipline | 0.121 | |||
Generalist nurse | 577 (54.4) | 260 (45.1) | 317 (54.9) | |
Nurse in anesthesia-resuscitation | 106 (10) | 39 (36.8) | 67 (63.2) | |
Emergency and critical care nurse | 66 (6.2) | 23 (34.8) | 43 (65.2) | |
Community health nurse | 30 (2.8) | 10 (33.3) | 20 (66.7) | |
Midwife | 41 (3.9) | 20 (48.8) | 21 (51.2) | |
Laboratory technician | 53 (5.0) | 20 (37.7) | 33 (62.3) | |
Radiology technician | 100 (9.4) | 55 (55.0) | 45 (45.0) | |
Ortho-prosthesis | 30 (2.8) | 14 (46.7) | 16 (53.3) | |
Kinesitherapy | 14 (1.3) | 6 (42.9) | 8 (57.1) | |
Social worker | 18 (1.7) | 5 (27.8) | 13 (72.2) | |
Nursing and health technique pedagogy | 26 (2.5) | 14 (53.8) | 12 (46.3) | |
Educational level | <0.001 | |||
Bachelor’ degree: 1st year | 505 (47.6) | 193 (38.2) | 312 (61.8) | |
Bachelor’ degree: 2nd year | 238 (22.4) | 101 (42.4) | 137 (57.6) | |
Bachelor’ degree: 3rd year | 292 (27.5) | 158 (54.1) | 134 (45.9) | |
Master’s degree: 2nd year | 26 (2.5) | 14 (53.8) | 12 (46.2) | |
Platform or application used | 0.622 | |||
Google Classroom | 254 (23.9) | 110 (43.3) | 144 (56.7) | |
Zoom Cloud Meeting | 52 (4.9) | 25 (48.1) | 27 (51.9) | |
Google Meet | 66 (6.2) | 29 (43.9) | 37 (56.1) | |
WhatsApp Messenger | 591 (55.7) | 267 (45.2) | 324 (54.8) | |
Edmodo and Whatsapp Messenger | 63 (5.9) | 23 (36.5) | 40 (63.5) | |
Zoom Cloud Meeting and Whatsapp Messenger | 35 (3.3) | 12 (34.3) | 23 (65.7) | |
Choice of gadget/device | 0.807 | |||
Laptop | 300 (28.3) | 128 (42.7) | 172 (57.3) | |
Computer | 18 (1.7) | 9 (50) | 9 (50) | |
Mobile | 736 (69.4) | 325 (44.2) | 411 (55.8) | |
Tablet | 7 (0.7) | 4 (57.1) | 3 (42.9) | |
Internet quality | 0.193 | |||
Excellent | 60 (5.7) | 25 (41.7) | 35 (58.3) | |
Good | 603 (56.8) | 252 (41.8) | 351 (58.2) | |
Bad | 398 (37.5) | 189 (47.5) | 209 (52.5) | |
Location of distance learning courses | 0.708 | |||
Home | 954 (89.9) | 415 (43.5) | 539 (56.5) | |
University campus | 34 (3.2) | 16 (47.1) | 18 (52.9) | |
Friends’ houses | 62 (5.8) | 31 (50.0) | 31 (50.0) | |
Leisure center | 11 (1.0) | 4 (36.4) | 7 (63.6) | |
Distance learning environment | <0.001 | |||
Slightly appropriate | 300 (28.3) | 116 (38.7) | 184 (61.3) | |
Appropriate | 419 (39.5) | 161 (38.4) | 258 (61.6) | |
Inappropriate | 342 (32.2) | 189 (55.3) | 153 (44.7) | |
No. of distance learning courses attended during the survey | 0.986 | |||
1 | 354 (33.4) | 154 (43.5) | 200 (56.5) | |
2–3 | 295 (27.8) | 129 (43.7) | 166 (56.3) | |
4–5 | 121 (11.4) | 55 (45.5) | 66 (54.4) | |
>6 | 291 (27.4) | 128 (44.0) | 163 (56.0) | |
Student engagement during distance learning | <0.001 | |||
High engagement | 623 (58.7) | 199 (31.9) | 424 (68.1) | |
Low engagement | 438 (41.3) | 267 (61) | 171 (39) |
Data are presented as mean±standard deviation or number (%).
Ispits: High Institute of Nursing Professions and Health Techniques.
Factors Associated with Students’ Self-determined Motivation during Distance Learning Using Univariate Analysis (N=1,061)
Variable | OR (95% CI) | p-value |
---|---|---|
Age (yr) | ||
<21 | 1.13 (0.81–1.59) | 0.470 |
>21 | Ref | |
Gender | ||
Male | 0.85 (0.65–1.10) | 0.210 |
Female | Ref | |
Ethnicity | ||
Moroccan | 0.30 (0.11–0.79) | 0.015 |
Other | Ref | |
Marital status | ||
Single | 0.43 (0.04–4.17) | 0.469 |
Married | 0.20 (0.02–2.44) | 0.222 |
Divorced | Ref | |
Higher education institute | ||
Ispits Marrakech | 1.250 (0.56–2.77) | 0.583 |
Ispits Guelmim | 1.953 (0.87–4.40) | 0.106 |
Ispits Laayoune | 1.525 (0.69–3.38) | 0.299 |
Ispits Agadir | Ref | |
Discipline | ||
Generalist nurse | 1.422 (0.65–3.13) | 0.381 |
Nurse in anesthesia-resuscitation | 2.004 (0.84–4.77) | 0.116 |
Emergency and critical care nurse | 2.181 (0.87–5.49) | 0.098 |
Community health nurse | 2.333 (0.79–6.88) | 0.125 |
Midwife | 1.225 (0.46–3.28) | 0.686 |
Laboratory technician | 1.925 (0.74–4.98) | 0.177 |
Radiology technician | 0.955 (0.40–2.27) | 0.916 |
Ortho-prosthetist | 1.333 (0.46–3.82) | 0.592 |
Physiotherapist | 1.556 (0.42–5.76) | 0.508 |
Social worker | 3.033 (0.84–10.99) | 0.091 |
Nursing and health technique pedagogy | Ref | |
Educational level | ||
Bachelor’ degree: 1st year | 1.886 (0.85–4.16) | 0.116 |
Bachelor’ degree: 2nd year | 1.583 (0.70–3.57) | 0.268 |
Bachelor’ degree: 3rd year | 0.989 (0.44–2.21) | 0.979 |
Master’s degree: 2nd year | Ref | |
Platform or application used | ||
Google Classroom | 0.683 (0.33–1.43) | 0.313 |
Zoom Cloud Meeting | 0.563 (0.23–1.36) | 0.204 |
Google Meet | 0.666 (0.28–1.56) | 0.348 |
Whatsapp Messenger | 0.633 (0.31–1.30) | 0.211 |
Edmodo and Whatsapp Messenger | 0.907 (0.38–2.16) | 0.826 |
Zoom Cloud Meeting and Whatsapp Messenger | Ref | |
Choice of gadget/device | ||
Laptop | 1.792 (0.39–8.15) | 0.450 |
Computer | 1.333 (0.23–7.74) | 0.749 |
Mobile | 1.686 (0.37–7.59) | 0.496 |
Tablet | Ref | |
Internet quality | ||
Excellent | 1.266 (0.73–2.19) | 0.400 |
Good | 1.260 (0.98–1.62) | 0.076 |
Bad | Ref | |
Site of distance learning courses | ||
Home | 0.742 (0.22–2.55) | 0.636 |
University campus | 0.643 (0.16–2.61) | 0.536 |
Friends’ houses | 0.571 (0.15–2.15) | 0.408 |
Leisure center | Ref | |
Distance learning environment | ||
Slightly appropriate | 1.959 (1.43–2.69) | <0.001 |
Appropriate | 1.980 (1.48–2.65) | <0.001 |
Inappropriate | Ref | |
No. of distance learning courses attended during the survey | ||
1 | 1.020 (0.76–1.40) | 0.902 |
2–3 | 1.011 (0.73–1.40) | 0.950 |
4–5 | 0.942 (0.61–1.44) | 0.785 |
>6 | Ref | |
Student engagement during distance learning | ||
High engagement | 3.327 (2.58–4.29) | <0.001 |
Low engagement | Ref |
OR: Odds ratio, CI: Confidence interval, Ref: Reference, Ispits: High Institute of Nursing Professions and Health Techniques.
p<0.05; The correlation is significant at the 0.05 level (two-tailed).
p<0.01; The correlation is significant at the 0.01 level (two-tailed).
Factors Affecting Students’ Self-determined Motivation during Distance Learning Using Multivariate Analysis (N=1,061)
Variable | β | SE | Wald | aOR (95% CI) | p-value |
---|---|---|---|---|---|
Ethnicity | |||||
Moroccan | −1.387446 | 0.550777 | 6.345723 | 0.25 (0.08–0.73) | 0.012 |
Educational level | |||||
1st year bachelor’s degree | 0.499502 | 0.179684 | 7.727843 | 1.65 (1.16–2.34) | 0.005 |
Distance learning environment | |||||
Slightly appropriate | 0.500497 | 0.178169 | 7.891114 | 1.65 (1.16–2.40) | 0.005 |
Appropriate | 0.502233 | 0.166281 | 9.122733 | 1.65 (1.19–2.29) | 0.003 |
Student engagement | |||||
High engagement | 1.067519 | 0.141007 | 57.315374 | 2.91 (2.21–3.80) | <0.001 |
SE: Standard error, aOR: Adjusted odds ratio, CI: Confidence interval.
Pearson Correlation Coefficients between Learning Motivation and Student Engagement (N=1,061)
Variable | Emotional engagement | Behavioral engagement | Cognitive engagement |
---|---|---|---|
Intrinsic motivation | 0.474 |
0.292 |
0.307 |
Identified regulation | 0.412 |
0.276 |
0.266 |
External regulation | −0.069 |
0.112 |
0.039 |
Amotivation | −0.102 |
−0.114 |
−0.129 |
p<0.05.
p<0.01.