Online learning system usage intention questionnaire (UTAUT)

Online learning and the university's learning management system (LMS) are easy topics for sampling because the main respondents are students. UTAUT brings performance, effort and social influence together in one widely tested model.

Research model

Model following UTAUT (Venkatesh et al., 2003): performance expectancy, effort expectancy and social influence affect behavioral intention. In the original UTAUT, facilitating conditions affect use behavior rather than intention, so they are not included in the intention model.

• Performance Expectancy → Behavioral Intention (positive)
• Effort Expectancy → Behavioral Intention (positive)
• Social Influence → Behavioral Intention (positive)

Questionnaire items

Original English wording. Answered on a 5-point Likert scale (1 = Strongly disagree … 5 = Strongly agree) unless the scale page says otherwise; (R) marks a reverse-coded item.

Performance Expectancy (PE) · UTAUT scale

Code	Item
PE1	I would find [system] useful in my job.
PE2	Using [system] enables me to accomplish tasks more quickly.
PE3	Using [system] increases my productivity.
PE4	If I use [system], I will increase my chances of getting a raise.

Source: Venkatesh et al. (2003). See UTAUT scale.

Effort Expectancy (EE) · UTAUT scale

Code	Item
EE1	My interaction with [system] would be clear and understandable.
EE2	It would be easy for me to become skillful at using [system].
EE3	I would find [system] easy to use.
EE4	Learning to operate [system] is easy for me.

Source: Venkatesh et al. (2003). See UTAUT scale.

Social Influence (SI) · UTAUT scale

Code	Item
SI1	People who influence my behavior think that I should use [system].
SI2	People who are important to me think that I should use [system].
SI3	The senior management of this business has been helpful in the use of [system].
SI4	In general, the organization has supported the use of [system].

Source: Venkatesh et al. (2003). See UTAUT scale.

Behavioral Intention (BI) · UTAUT scale

Code	Item
BI1	I intend to use [system] in the next <n> months.
BI2	I predict I would use [system] in the next <n> months.
BI3	I plan to use [system] in the next <n> months.

Source: Venkatesh et al. (2003). See UTAUT scale.

Tips

• The four original performance expectancy items are written for employees (job, pay raise); this template rewrites them for studying and keeps the original items below for comparison. State the adaptation clearly in Chapter 3.
• If the university makes the system mandatory, intention to use will vary little; consider measuring satisfaction or continuance intention instead.
• Name the specific system (for example the university LMS or Google Classroom) in the screening question.

Work out the minimum sample size for this model; once the data are in, clean the responses and run the survey data analysis for your results chapter.

Studies that used this model

• Pham, Le and Vo (2023). Determinants of Online Education Technology Acceptance Among Vietnamese Undergraduates: A UTAUT-Typed Model Analysis. Vietnam Journal of Education, 7(3), 288–301. Sample: 232 university students, stratified sampling; CFA and SEM. Reliability: α 0.81-0.89 (Table 5).
• Cao and Nguyen (2022). Factors Affecting Students in Vietnam's Intention on Using Smartphones for Learning on the Mobile Learning Platforms. Journal of Educational and Social Research, 12(2), 113–125. Sample: 831 students; UTAUT2 for mobile learning; PLS-SEM. Reliability: CR 0.906-0.962 (section 4.2.1).
• Nguyen, Nguyen and Cao (2014). Acceptance and use of cloud-based e-learning (article in Vietnamese). Tạp chí Phát triển Khoa học và Công nghệ, ĐHQG-HCM, 17(3), 71–87. Sample: 282 e-learning users, about half aged 19-23; UTAUT2. Reliability: α 0.685-0.830 (section 4.2.1).

Collecting responses

If your own network cannot reach the target respondents, you can pay for verified responses through Genius Data (referral link, we may earn a commission), paying only for approved responses.