PTDoes knowing how to use technology help people work better?
At a Brazilian public financial institution, 356 employees in technology and in social programmes rated their own digital competence, how useful and easy they find technology, and their own performance. The dissertation measures how the three are linked and where gaps by age, gender and department appear. Explained in 12 screens.
Skill, usefulness and performance are three different things
Almost every study of digital competence was done in schools and universities. The author takes the question into a company and tests an idea that, as far as the author found, no one had tested: part of the effect of competence on performance would run through use of technology. Tap a block or an arrow:
Model in Figure 5 and hypotheses H1 to H4 (sections 2.3 to 2.6). Hypotheses H5 to H7, on age, gender and department, were tested separately by comparing means.
A questionnaire made for students, adjusted for a bank
The questionnaire came from a Spanish study of university students, based on the European DigComp framework, with five areas. Colleagues at the company pointed out what made sense at work. Move through the stages and tap an area:
Height = number of questions; the hollow box holds the questions of the original version. Sections 3.2.1, 3.2.1.1 and 3.3 and Tables 4, 5 and 20. The dissertation speaks of 27 questions in the final version; counting from the tables gives 26 (our count).
356 employees from two very different departments
The research took place at a Brazilian public financial institution, which is not named. In March and April 2025, an anonymous questionnaire went to the Information Technology department, where a lot of digital competence is expected, and to Social Programmes, which serves recipients of government programmes across the country. The HR department was also invited, but few answered and it was left out.
Sections 3.1 and 3.5 and Tables 17 to 19. Social Programmes: 195 answers, 189 valid, out of 1,757 employees (about 11%, our calculation). IT: 179 answers, 167 valid, out of 3,724 (about 4.5%, our calculation). The minimum calculated for the tests was 43.
Social Programmes · 189
IT · 167
One dot per person; counts from Tables 17 and 18. The order of the dots within each department is just for reading.
Answer like a participant
Five real questions from the questionnaire, each with its own scale: 1 to 4 for competence, 1 to 7 for technology and 1 to 10 for performance. The mean of the 356 appears after your answer.
Questions 16 and 13 on digital competence, 4 and 6 on use of technology and 9 on performance (Appendices VI to VIII); means from Tables 20, 21 and 22. Each scale was drawn at the same width to compare positions. Questions translated by us from the Portuguese questionnaire.
High scores for communicating and lower ones for creating content
On a 1 to 4 scale, the overall mean of digital competence was 2.90. Employees feel confident communicating and staying safe; creating content and solving technical problems came lower. For performance, from 1 to 10, the mean was 7.97. Switch the measure and tap a bar:
The floor is 1 and the hollow box goes up to the top of the scale (4 or 10). Means from Tables 20 and 22, only with the questions that stayed in the model. Performance was reported by the employees themselves.
All four hypotheses were confirmed
With structural equation modelling, the author tested the links all at once. People who rate their digital competence higher also find technology more useful and easy and report higher performance. The weakest link is between use and performance. Tap an arrow:
Standardised coefficients (β) of the final model, Table 35 and Figure 7 (SmartPLS 4, 10,000 resamples). Thickness ∝ β. R² = how much of the differences between people the model explains.
Most of the effect goes straight to performance
Digital competence is linked to performance along two paths. The direct one is worth 0.412. The one through use of technology is worth 0.066: it is significant, but it is about one seventh of the total. Before seeing the name statistics gives this, choose:
Table 34: direct 0.412, indirect 0.066 (p = 0.016), total 0.478. Indirect = 0.486 × 0.135. The share via technology (about 14% of the total) is our calculation. Illustrative reading, all else equal; association at a single point in time.
Almost everyone finds technology useful, but not everyone finds it easy
Use of technology was measured with eight sentences, from 1 to 7: four on usefulness and four on ease. Before you look, a guess: which sentence got the lowest score?
Effect size (f²) from the first model, Table 31: 0.188 is medium and 0.020 is small, by the Cohen criteria the author uses. Our reading: since almost everyone agrees that technology is useful, with little variation, that part of the measure has little to explain about differences in performance.
Dot = mean; light band = mean ± 1 standard deviation (cut at the scale). Table 21; sentences from Appendix VII, translated by us. The wide band of the sentence on mental effort (standard deviation of 1.94) shows answers spread from end to end.
Men and IT staff rate themselves slightly higher
The dissertation did not look at access to technology but at the ability to use it, the so-called second-order digital divide. On average, men rated themselves above women, and IT above Social Programmes. Before you look, a guess: in which area was the gap between men and women largest?
t-tests from Tables 38 and 39. Striped = difference not significant. On the full scale (1 to 4) you can see the real size of the gaps; the zoom enlarges the stretch from 2 to 3.5.
Only the group aged 60 or over scored lower, and narrowly
The hypothesis was that younger people would have more digital competence. Across the groups up to age 59, the means barely change. The group aged 60 or over, with 33 people, scored below those aged 40 to 49 and 50 to 59, right at the edge of significance. Tap a group or switch the view:
Means and 95% intervals from Table 43; Tukey comparisons from Table 42 (ANOVA with p = 0.050, Table 41). Scale cut between 2.4 and 3.2 to show the differences, which are small on a 1 to 4 scale.
Train those with less digital skill
For the author, the results support training programmes aimed at those with less command of technology, which also look after engagement and confidence in using it, in line with SDG 10 on reducing inequalities.
For the company
- The adapted questionnaire can serve as a diagnosis to guide action, the author says.
- The lowest scores were in creating content (2.37) and solving technical problems (2.79); the highest, in communicating (3.24) and staying safe (3.19).
For those who look after people
- Training is not just teaching the tool: the author asks for attention to confidence in use.
- Self-assessments can mislead: according to studies the author cites, men tend to overestimate and women to underestimate what they know, and stereotypes weigh on older workers.
For society
- The research looked at the divide in the ability to use technology, not in access to it, and found it among colleagues at the same company.
- Social Programmes serves recipients through digital channels: the competence of those who serve reaches the public.
What this research does not say
- One company, two departments. And ages concentrated in mid-career; other sectors and organisations may differ. · according to the author
- It is all self-assessment. Competence and performance were reported by the people themselves; the author suggests adding company indicators and peer review. · according to the author
- A single point in time. It shows what goes together, not what causes what; the author suggests following people over time. · according to the author
- "Use" is an opinion about technology. The measure asks whether it is useful and easy, not how much people use it. · our observation
- Gender and department overlap. IT is 62% men and Social Programmes 60% women; each comparison looks at one factor at a time. · our observation, Table 17
Credits
BARROS, Daniela Sakashita de. Explorando as relações entre competências digitais, uso da tecnologia e desempenho no trabalho em uma instituição financeira. Master's dissertation (Business Administration), Universidade Presbiteriana Mackenzie, São Paulo, 2025. Advisor: Prof. Dr. Darcy Mitiko Mori Hanashiro.
Dissertation approved on 4 August 2025. The studies were funded by the public financial institution where the author works. Questionnaires translated and back-translated by specialised firms; data analysed in SmartPLS 4, Jamovi and SPSS. This version simplifies the work for the general public.