| Literature DB >> 31920872 |
Andrés Fuster-Guilló1, María Luisa Pertegal-Felices2, Antonio Jimeno-Morenilla1, Jorge Azorín-López1, María Luisa Rico-Soliveres1, Felipe Restrepo-Calle3.
Abstract
Gamification methods adapt the mechanics of games to educational environments for the improvement of the teaching-learning process. Serious games play an important role as tools for gamification, in particular in the context of software engineering courses because of the idiosyncratic nature of the topic. However, the studies on the improvement of student performance resulting from the use of gamification and serious games in courses with different contexts are not conclusive. More empirical research is thus needed to obtain reliable results on the effectiveness, benefits and drawbacks. The overall objective of this work is to study the benefits generated by serious games in the teaching-learning process of Computer Engineering degrees, analyzing the impact on the motivation and student satisfaction, as well as on the learning outcomes and results finally achieved. To this end, an intervention is proposed in the subject of Computer Architecture based on two components covering theoretical and practical sessions. In the theoretical sessions, a serious game experience using Kahoot has been introduced, complementing the master classes and class exercises. For the practical sessions, the development of projects with groups of students has been proposed, whose results in terms of computer performance can be compared through a competition (hackathon). Evaluation of the serious game-based intervention has been approached in terms of student satisfaction and motivation, as well as improved academic performance. In order to assess student satisfaction, surveys have been used to assess the effect on student motivation and satisfaction. For the evaluation of academic performance, a comparative analysis between an experimental and a control group has been carried out, noting a slight increase in the experimental group students' marks.Entities:
Keywords: computer engineering; gamification; motivation; serious games; teaching-learning
Year: 2019 PMID: 31920872 PMCID: PMC6923676 DOI: 10.3389/fpsyg.2019.02843
Source DB: PubMed Journal: Front Psychol ISSN: 1664-1078
Satisfaction survey questions and answers about Kahoot use.
| Q1Resp1 | When I play Kahoot | “I have fun but I don’t learn” |
| Q1Resp2 | “I have fun and I learn” | |
| Q1Resp3 | “I don’t have fun but I learn” | |
| Q1Resp4 | “I don’t have fun or learn” | |
| Q2Resp1 | Making Kahoots helps me reinforce what I learned in class | “It doesn’t help me at all” |
| Q2Resp2 | “It helps me a little” | |
| Q2Resp3 | “It helps me” | |
| Q2Resp4 | “It helps me a lot” | |
| Q3Resp1 | Making Kahoots motivates me to learn the subject | “Nothing” |
| Q3Resp2 | “Little” | |
| Q3Resp3 | “Quite a lot” | |
| Q3Resp4 | “A lot” | |
| Q4Resp1 | I prefer to do the Kahoot | “As soon as class starts” |
| Q4Resp2 | “In the middle of class” | |
| Q4Resp3 | “At the end of class” | |
| Q5Resp1 | I would like the Kahoot’s length to be | “Short (<5 min)” |
| Q5Resp2 | “Medium (between 5 and 15 min)” | |
| Q5Resp3 | “Long (>15 min)” | |
| Q6Resp1 | I prefer the teacher to use to explain the theory | “Exclusively his explanation” |
| Q6Resp2 | “His explanation combined with Kahoot” | |
| Q6Resp3 | “His explanation combined with practical exercises” | |
| Q6Resp4 | “His explanation combined with Kahoot and practical exercises” | |
| Q7Resp1 | In general, I consider Kahoot to be | “Unnecessary” |
| Q7Resp2 | “Unimportant” | |
| Q7Resp3 | “Necessary” | |
| Q7Resp4 | “Essential” |
List of Kahoot quizzes for each theoretical session.
| Kahoot1: Session1 | Initial concepts | T1. Introduction |
| Kahoot2: Session2 | Performance | T2. Performance |
| Kahoot3: Session3 | Amdahl | T2. Performance |
| Kahoot4: Session4 | CPU Performance | T2. Performance |
| Kahoot5: Session5 | Instruction Set Architecture ISA | T3. Instruction Set Architecture |
| Kahoot6: Session6 | Instruction Set Architecture ISA 2 | T3. Instruction Set Architecture |
| Kahoot7: Session7 | Introducing segmentation | T4. Segmentation |
| Kahoot8: Session8 | Segmented performance | T4. Segmentation |
| Kahoot9: Session9 | Pipeline segmentation | T4. Segmentation |
| Kahoot10: Session10 | Satisfaction survey | |
| Kahoot11: Session11 | Pipeline segmentation 2 | T4. Segmentation |
| Kahoot12: Session12 | Pipeline segmentation 3 | T4. Segmentation |
| Kahoot13: Session13 | Memory 1 | T5. Memory |
| Kahoot14: Session14 | Memory 2 | T5. Memory |
| Kahoot15: Session15 | Input Output | T6. Input Output |
FIGURE 1Percentage distribution of responses to the question 1.
FIGURE 2Percentage distribution of responses to the question 2.
FIGURE 3Percentage distribution of responses to the question 3.
FIGURE 4Percentage distribution of responses to the question 4.
FIGURE 5Percentage distribution of responses to the question 5.
FIGURE 6Percentage distribution of responses to the question 6.
FIGURE 7Percentage distribution of responses to the question 7.
Test of inter-subject effects.
| Intersection | 12888.686 | 1 | 1849.842 | 0.000 |
| Group | 9.516 | 1 | 1.366 | 0.244 |
| Error | 1079.955 | 155 |
Test of intra-subject effects.
| Apl | 26.390 | 1 | 11.572 | 0.001 | 0.069 | 0.922 |
| Gr × Apl | 41.450 | 1 | 18.176 | 0.000 | 0.105 | 0.989 |
| Error | 353.469 | 155 |
Student’s t-test on the difference of means between the experimental and control groups.
| PRE | 0.951 | 155 | 0.343 | –0.380 | 0.399 |
| POST | –4.323 | 155 | 0.000 | 1.079 | 0.249 |
FIGURE 8Academic performance score (out of a maximum of 10) of the groups at pretest (PRE) and posttest (POST).