Attractiveness of Collaborative Platforms for Sustainable E-Learning in Business Studies
Abstract
:1. Introduction
2. Theoretical Background
2.1. E-Learning Collaboration Platforms
- “Together mode”, which offers a simulation of actual meeting members being in the same room;
- Customisable meetings that support setting up breakout rooms for meeting in smaller groups;
- Ability to record the meetings on the go, accompanied with meeting notes and transcripts.
2.2. Attractiveness of E-Learning Collaboration Platforms for Students
- Saved time—Being able to finish a process or a task faster automatically means saving time and, as such, means fewer costs;
- Strengthened team relationships—One can see students enrolled in a course as closely connected groups. So, it comes to be very valuable to be capable of maintaining sound and effective relationships within groups of participants. With modern collaboration tools, this can be supported and elevated so that every student has a better understanding of teamwork and mutual goals, of course, he attends;
- Better organisation of teaching work—Collaboration tools are facilitators to improve teaching, especially active learning.
2.3. User Experience
2.4. Research Model
3. Methodology
3.1. Participants and Procedure
3.2. Measurement Instrument
3.3. Data
4. Results
4.1. Reflective Measurement Model Assessment
4.2. Structural Model Assessment
4.3. The Importance—Performance Map Analysis (IPMA)
5. Discussion
5.1. Implication of the Study
5.2. Limitations and Suggestions for Future Work
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Term | Description with Examples |
---|---|
UX principles | Critical factors and basic concepts indicate the understanding of the user experience, which professionals must consider in their work. Example: The hedonic and pragmatic aspects of software application development play an essential role in user experience design as user experience is temporary. |
UX practices | Includes actions that practitioners need to perform to comply with the user experience principles. Examples of practices are: recognizing users’ personal goals and desires, preparing prototypes, including users in the design process, and assessing software from a hedonistic and pragmatic perspective. |
UX software | Computer-aided software that developers or designers use to perform a variety of UX practices is usually designed to support specific methods to allow for more systematic software development. Examples: eye-tracking software, persona preparation, visual design, and prototyping software. |
UX techniques | They allow practitioners to select and load a structure based on best practices, thus allowing them to be more systematic, and therefore, they are also more likely to succeed. Examples are questionnaires and surveys, mind plans, cognitive mapping, field research, and design studio. |
When | What | How |
---|---|---|
Prior to use | Anticipated user experience | Expectations about the experience. |
During use | Momentary user experience | Facing with the experience. |
After usage | Episodic user experience | Thinking about the experience. |
Past use | Cumulative user experience | Call to mind several periods of use. |
Factors | Description | Items (Measured Variable Codes) |
---|---|---|
Perceived efficiency (EF) | The degree to which users can solve tasks without unnecessary effort. | EF1: The e-learning platform works fast. |
EF2: The e-learning platform is efficient to use. | ||
EF3: The e-learning platform is practical to use. | ||
EF4: The e-learning platform is organised. | ||
Perceived perspicuity (PE) | The degree of ease in getting acquainted with the e-learning platform and learning to use it. | PE1: The e-learning platform is understandable to use. |
PE2: The e-learning platform is easy to learn. | ||
PE3: The e-learning platform is easy to use. | ||
PE4: The e-learning platform is transparent. | ||
Perceived dependability (DE) | The degree to which the user feels in control of the interaction with the e-learning platform. | DE1: The e-learning platform is predictive. |
DE2: The e-learning platform is supportive. | ||
DE3: The e-learning platform is secure. | ||
DE4: The e-learning platform meets expectations. | ||
Perceived stimulation (SI) | The degree of excitement and motivation the user perceives when using the e-learning platform. | SI1: The e-learning platform is valuable. |
SI2: An e-learning platform is exciting. | ||
SI3: An e-learning platform is interesting. | ||
SI4: An e-learning platform is motivating. | ||
Perceived novelty (NO) | The degree to which the e-learning platform is innovative and creative attracts users’ interest. | NO1: The e-learning platform encourages creativity. |
NO2: An e-learning platform is inventive. | ||
NO3: An e-learning platform is leading edge. | ||
NO4: An e-learning platform is innovative. | ||
Perceived attractiveness (AT) | The degree of the user’s general impression of the e-learning platform. | AT1: The e-learning platform is enjoyable to use. |
AT2: The e-learning platform is good to use. | ||
AT3: The e-learning platform is pleasing to use. | ||
AT4: The e-learning platform is pleasant to use. | ||
AT5: The e-learning platform is attractive to use. | ||
AT6: The e-learning platform is friendly to use. |
Constructs | Item | Mean Value | Standard Deviation | Indicators Loadings | Indicator Reliability | HTMT Confidence Interval | |
---|---|---|---|---|---|---|---|
2.5% | 97.5% | ||||||
Perceived efficiency (EF) | EF1 | 5.258 | 1.655 | 0.723 | 0.523 | 0.264 | 0.315 |
EF2 | 5.534 | 1.489 | 0.793 | 0.629 | 0.327 | 0.380 | |
EF3 | 5.355 | 1.595 | 0.763 | 0.582 | 0.289 | 0.338 | |
EF4 | 5.524 | 1.604 | 0.766 | 0.587 | 0.325 | 0.388 | |
Perceived perspicuity (PE) | PE1 | 5.817 | 1.488 | 0.817 | 0.667 | 0.315 | 0.363 |
PE2 | 5.399 | 1.787 | 0.753 | 0.567 | 0.260 | 0.319 | |
PE3 | 5.412 | 1.655 | 0.764 | 0.584 | 0.255 | 0.306 | |
PE4 | 5.386 | 1.744 | 0.795 | 0.632 | 0.337 | 0.396 | |
Perceived dependability (DE) | DE2 | 5.483 | 1.613 | 0.751 | 0.564 | 0.435 | 0.534 |
DE3 | 5.551 | 1.628 | 0.747 | 0.558 | 0.325 | 0.400 | |
DE4 | 5.395 | 1.573 | 0.82 | 0.672 | 0.413 | 0.483 | |
Perceived stimulation (SI) | SI1 | 4.851 | 1.592 | 0.778 | 0.605 | 0.296 | 0.342 |
SI2 | 4.448 | 1.553 | 0.818 | 0.669 | 0.268 | 0.304 | |
SI3 | 4.959 | 1.621 | 0.874 | 0.764 | 0.333 | 0.370 | |
SI4 | 4.596 | 1.738 | 0.752 | 0.566 | 0.261 | 0.306 | |
Perceived novelty (NO) | NO1 | 4.642 | 1.786 | 0.857 | 0.734 | 0.579 | 0.676 |
NO2 | 4.647 | 1.794 | 0.82 | 0.672 | 0.517 | 0.614 | |
Perceived attractiveness (AT) | AT1 | 5.546 | 1.516 | 0.758 | 0.575 | 0.185 | 0.208 |
AT2 | 5.615 | 1.583 | 0.789 | 0.623 | 0.199 | 0.226 | |
AT3 | 5.143 | 1.522 | 0.799 | 0.638 | 0.184 | 0.210 | |
AT4 | 5.452 | 1.448 | 0.821 | 0.674 | 0.200 | 0.221 | |
AT5 | 5.006 | 1.594 | 0.825 | 0.681 | 0.203 | 0.227 | |
AT6 | 5.223 | 1.546 | 0.83 | 0.689 | 0.199 | 0.226 |
Construct | Internal Consistency Reliability | Convergent Validity | |
---|---|---|---|
Cronbach’s Alpha | Composite Reliability | AVE | |
0.60–0.95 | 0.60–0.95 | >0.50 | |
Perceived efficiency (EF) | 0.759 | 0.847 | 0.58 |
Perceived perspicuity (PE) | 0.790 | 0.863 | 0.613 |
Perceived dependability (DE) | 0.667 | 0.817 | 0.598 |
Perceived stimulation (SI) | 0.820 | 0.881 | 0.651 |
Perceived novelty (NO) | 0.579 | 0.826 | 0.703 |
Perceived attractiveness (AT) | 0.891 | 0.916 | 0.647 |
EF | PE | DE | SI | NO | AT | |
---|---|---|---|---|---|---|
Perceived efficiency (EF) | 0.762 | |||||
Perceived perspicuity (PE) | 0.752 | 0.783 | ||||
Perceived dependability (DE) | 0.739 | 0.676 | 0.774 | |||
Perceived stimulation (SI) | 0.633 | 0.579 | 0.584 | 0.807 | ||
Perceived novelty (NO) | 0.491 | 0.431 | 0.447 | 0.659 | 0.839 | |
Perceived attractiveness (AT) | 0.744 | 0.753 | 0.722 | 0.786 | 0.619 | 0.804 |
Constructs | Explained Variance R2 Value | Effect Size f2 Value | Predictive Relevance Q2 Value |
---|---|---|---|
Weak (≥0.25) Moderate (≥0.50) Substantial (≥0.75) | Small (≥0.02) Medium (≥0.15) High (≥0.35) | Small (>0.00) Medium (≥0.25) Large (≥0.50) | |
Perceived efficiency (EF) | 0.104 | ||
Perceived perspicuity (PE) | 0.104 | ||
Perceived dependability (DE) | 0.036 | ||
Perceived stimulation (SI) | 0.259 | ||
Perceived novelty (NO) | 0.035 | ||
Perceived attractiveness (AT) | 0.805 | 0.516 |
Constructs Impact on Perceived Attractiveness (AT) | Path Coefficients (β) | t-Statistics | p-Values | 95% Confidence Intervals | Significant (p < 0.00) |
---|---|---|---|---|---|
≥0.10 | ≥1.96 | <0.001-Strong <0.01-Moderate <0.05-Weak ≥-No Effect | [2.5%, 97.5%] | Yes/No | |
Perceived efficiency (EF) | 0.254 | 7.533 | 0.000 | [0.187, 0.321] | Yes |
Perceived perspicuity (PE) | 0.226 | 6.279 | 0.000 | [0.156, 0.299] | Yes |
Perceived dependability (DE) | 0.130 | 4.375 | 0.000 | [0.071, 0.191] | Yes |
Perceived stimulation (SI) | 0.346 | 11.358 | 0.000 | [0.285, 0.405] | Yes |
Perceived novelty (NO) | 0.110 | 4.557 | 0.000 | [0.065, 0.158] | Yes |
Importance | Performances | |
---|---|---|
Perceived efficiency (EF) | 0.254 | 73.847 |
Perceived perspicuity (PE) | 0.226 | 75.372 |
Perceived dependability (DE) | 0.13 | 74.509 |
Perceived stimulation (SI) | 0.346 | 62.164 |
Perceived novelty (NO) | 0.11 | 60.742 |
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Sternad Zabukovšek, S.; Deželak, Z.; Parusheva, S.; Bobek, S. Attractiveness of Collaborative Platforms for Sustainable E-Learning in Business Studies. Sustainability 2022, 14, 8257. https://doi.org/10.3390/su14148257
Sternad Zabukovšek S, Deželak Z, Parusheva S, Bobek S. Attractiveness of Collaborative Platforms for Sustainable E-Learning in Business Studies. Sustainability. 2022; 14(14):8257. https://doi.org/10.3390/su14148257
Chicago/Turabian StyleSternad Zabukovšek, Simona, Zdenko Deželak, Silvia Parusheva, and Samo Bobek. 2022. "Attractiveness of Collaborative Platforms for Sustainable E-Learning in Business Studies" Sustainability 14, no. 14: 8257. https://doi.org/10.3390/su14148257