Student motivation is one of the central topics within the field of general education. It is vital to understand factors affecting students’ motivation as it can be regarded as one of the pillars of the good performance. Researchers have paid significant attention to the problem and its manifold facets have been discussed extensively. Researchers have analyzed motivation in terms of particular disciplines, the relationships with teachers or peers, teacher training as well as the use of technology. Scholars employ various research methods to address their questions. This paper includes a brief analysis of a number of studies and a more detailed evaluation of one of the articles with the focus on the methodology.
Types of Motivation and Performance
The purpose of the study in question was to identify the way different types of motivation affected Greek students’ performance in PE classes (Barkoukis, Taylor, Chanal & Ntoumanis, 2014). The researchers focused on controlling (grades, perceptions of others) and autonomous (intrinsic) types of motivation. Barkoukis et al. (2014) utilized a three-year longitudinal design that included 354 Greek high school students.
The researchers developed four hypotheses. First, they hypothesized that the grades would increase each year. The researchers also hypothesized that intrinsic motivation would have a positive effect on students’ performance. The third hypothesis was based on the assumption that controlling motivation would have adverse effects on students’ grades. Finally, the researchers expected that amotivation (no motivation) and external regulation would have a negative impact on students’ grades.
The students’ grades and motivation levels were recorded at the beginning and the end of each of the three years. Modified versions of the Academic Motivation Scale (its amotivation subscale) and the Self-Regulation Questionnaire were used to measure students’ motivation. Barkoukis et al. (2014) reported that the four hypotheses were proved to be true as intrinsic motivation positively affects students’ performance while controlling motivation is associated with poorer grades.
It is necessary to note that the sample size is quite significant, and the findings can be generalized (though, further research can provide more insights into the way demographics of students and other factors can be relevant). Nonetheless, the study is still associated with a significant limitation. The grading system of Greek schools is characterized by a small range of grades, which makes the results rather questionable and not very informative. At that, the implementation of similar research in US schools can provide valuable insights into the correlation between motivation and students’ performance (grades). One of the central benefits of the study is the use of a 3-year longitudinal study as similar studies are mainly based on data collected during shorter periods.
Teacher-Student Relationships and Students’ Motivation
This study’s purpose is to explore the way such components of teacher-student relationships as involvement and rejection during the first year of the secondary school. It is noteworthy that Maulana, Opdenakker, Stroet and Bosker (2013) explore the link between motivation and teacher-student relationship in the cross-national setting as Indonesian and Dutch teachers participated. Maulana et al. (2013) hypothesize that teachers’ involvement will positively correlate with students’ motivation and, vice versa, teachers’ rejection will negatively affect students’ motivation. Another hypothesis is concerned with the cultural aspect as researchers expect that there will be a clear variability between countries over time as regards teachers’ rejection and involvement.
The researchers utilize the quantitative research design as students’ questionnaires and encoded video-recorded lessons are analyzed. Ten Indonesian (2 males and 8 females) and ten Dutch teachers (five males and five females), as well as 337 Dutch students and 376 Indonesian students between 11 and 13 years old, took part in the research (Maulana et al., 2013). Overall, 24 classes (12 in each country) were video recorded, and four recordings were analyzed. The so-called, “real time” coding approach was utilized for the analysis of videotapes. When coding the videos, a modified version of Teacher as Social Context instrument was utilized. Self-reporting was the tool used to measure changes in students’ motivation.
The researchers state that their hypotheses have proved to be true as it was found that there is a strong link between teacher-student relationships and students’ motivation. The cultural background also had a significant impact on the results as Indonesian teachers displayed a slightly lower degree of involvement. The study has various implications as teachers can reconsider their involvement and rejection levels.
At the same time, the research is characterized by a number of limitations. First, the sample size (when it comes to teachers) is rather small as only ten teachers participated. Furthermore, the participating Indonesian teachers’ were mainly females, which could also affect the study’s results. The participation of teachers was voluntary, which also poses certain threats to the validity as the participants who agreed to take part in the research could believe that teachers should display a significant level of involvement. The teachers were also aware of the presence of the camera, which also puts a threat to the validity of the study. The use of self-reports could also hinder the validity of the research as students (especially Indonesian ones) could give socially desirable answers.
Technology and Motivation
The purpose of the study in question is to identify the way the use of mobile devices affected students’ intrinsic and extrinsic motivation (Ciampa, 2013). The researcher puts the following research question: “What do elementary teachers and students perceive as the motivational affordances of using mobile devices for learning?” (Ciampa, 2013, p. 2). The qualitative research design is utilized. The researcher presents findings of the beginning (5 months) of a 3-year longitudinal study.
Ciampa (2013) employs the case study design and focuses on a school characterized by students’ high academic achievements. A teacher and her ten students participated in the research. The data collection methods used include interviews and the analysis of the teacher’s blog. It is reported that the central factors associated with technology and affecting students’ motivation were cooperation, competition, recognition, challenge, curiosity, and control.
This study is characterized by a number of limitations. The sample size is very small, which makes it hardly generalizable. More importantly, the researcher does not include a control group, which could increase the validity of the research. Ciampa (2013) also states that the use of a new type of technology could make students more motivated as new methods are always associated with increased motivation. This study can have various implications as practitioners can learn about particular factors contributing to the improvement of students’ motivation when it comes to the use of technology in the classroom.
The purpose of another study under analysis is to evaluate the effectiveness of a teacher training intervention aimed at increasing students’ motivation (Kiemer, Gröschner, Pehmer & Seidel, 2015). This empirical study is based on the use of the mixed research methodology and the implementation of a true experiment. The researchers examine whether a video-based TPD (teacher professional development) intervention is effective in increasing students’ motivation as well as changing teachers’ approaches to the issue. Kiemer et al. (2015) put four research questions. First, Kiemer et al. (2015) investigate whether teachers’ practices in the intervention group transform into more “dialogic teaching” (with a focus on feedback and questioning) as a result of the intervention as compared with the teachers in the control group (p. 96). Secondly, the researchers investigate whether a one-year intervention has a positive impact on students’ motivation as compared with the students in the control group.
The third research question is concerned with the changes that occur during the intervention as regards students’ views on their teacher’s support and their “self-determined-learning motivation” (Kiemer et al., 2015, p. 97). Finally, the fourth research question is concerned with the nature of the changes in students’ motivation (they try to find out if they are systematical). It is necessary to note that the research questions are relevant to the purpose of the study, which is to identify the effectiveness of the teacher intervention, as they can be seen as the criteria of the researchers’ evaluation of the program.
As far as the methodology of the study, the researchers used the quasi-experimental design (as the samples were not selected randomly, but convenience sampling was employed. Ten teachers of mathematics and science in “middle or high-tracked schools” in Germany and their 226 students took part in the study (Kiemer et al., 2015, p. 97). The teachers could also choose whether they had the TPD intervention or a number of workshops, but they did not know which of these were the control and intervention group. The participants completed questionnaires that consisted of 4-point-Likert scale, and another data collection tool was the analysis of videos with the focus on the interaction between teachers and students. The data collection process was based on the one-year longitudinal design. It is possible to note that the methodology is consistent with the research questions and the purpose of the study as they researchers focus on motivation and interaction.
This study is characterized by some limitations. First, the sample size is very small, and the data are not generalizable. The reliance on self-reports is also a limitation as students could provide answers to please their teachers. The researchers note that these threats to validity are yet to be addressed in future studies through the use of a larger sample, “teacher reports, behavioral indicators” as well as experience sampling (Kiemer et al., 2015, p. 101). It is necessary to note that the researchers answered the four research questions and found that the intervention was effective as it improved the performance and motivation of students and teachers. This study can be of particular interest as it focuses on the motivation of both teachers and students, and, what is important, students are aware of their teachers’ effort to improve, which has certain effects on their performance and commitment.
Students’ Motivation and Academic Well-being
This study’s purpose is to examine the way a type of students’ motivation affects their academic well-being during their transition to upper classes. Tuominen-Soini, Salmela-Aro and Niemivirta (2012) focus on such domains as school burnout, schoolwork engagement, satisfaction and school value. This study is based on the use of quantitative methodology. The authors put four research questions. First, the researchers focus on the type of motivation. Secondly, Tuominen-Soini et al. (2012) concentrate on the stability of students’ motivation across their transition to upper classes. The third question is concerned with the way students with different types of motivation differ in terms of their academic well-being. Finally, the researchers try to identify the relationship between the change in the type of motivation and the change in the academic well-being.
The research involved the participation of 579 Finnish students who faced the transition from comprehensive school to the upper school. The participants completed questionnaires concerning their motivation and academic well-being. Tuominen-Soini et al. (2012) identified such types of motivation as success-orientation, mastery-orientation, avoidance-orientation and indifference. It was found that these profiles did not undergo meaningful changes during the transition. Success- and mastery-oriented students believed that their school experiences were meaningful, and they were significantly engaged in schoolwork. Avoidance-oriented and indifferent students did not display any meaningful correlation between their motivation type and academic well-being. The researchers also note that success-oriented students are characterized by a significant degree of school burnout.
Although the sample size is significant, the researchers note that future studies should focus on students in different countries as educational contexts vary. Self-reporting also poses certain threats to the research validity, and researchers should utilize a variety of data collection methods to gain insights into students’ academic well-being. The implications of this study are manifold, but they are mainly associated with the use of teaching methods to increase a particular type of motivation to ensure students’ appropriate academic well-being.
All the studies have contributed significantly to the development of the knowledge base concerning students’ motivation. One of these studies has a particular merit as it is concerned with the use of technology. It may seem that this issue has become ubiquitous, but it is still unclear whether particular types of devices have a positive influence on students’ motivation especially when it comes to considerable periods. Ciampa (2013) attempted to explore the effects of mobile devices on students’ motivation. This study could be improved in a number of ways.
First, it is important to slightly change the focus of the research as it is made on students’ motivation solely. Instead, it can be effective to explore the way teachers’ involvement or rejection is affected by the use of mobile devices. It has been acknowledged that these factors contribute significantly to the development of students’ motivation (Maulana et al., 2013). Of course, this aspect also involves the number of participants. Thus, at least, ten teachers and two classes of each of the educators should take part in the research. Each teacher will have an intervention and control group. It could be a good idea to carry out the study in different states, but it is also possible to confine the research to a particular city or state.
Random selection of teachers is vital as volunteers can be biased. Of course, the teachers selected will still give their consent and will be aware of the details of the research. However, the random sample will increase the validity while the rest of the factors cannot be avoided.
Finally, the use of cameras can affect the performance and reporting of the participants. However, it is possible to address this threat. The participants can understand that their classes are video-recorded, but they should know that the lessons are video recorded randomly. Therefore, the teachers will have to be outperforming every single class, or they can behave in a usual way. The degree of the teachers’ weariness will also be traced, especially if teachers try to outperform during all of their lessons.
The researchers should not simply rely on self-reports of the participants, but try to employ more generalizable tools. Quantitative research design would be the most appropriate option for the new study. First, the research should include the true experiment to make sure that the mobile device affects students’ motivation not the teachers’ instructions or other aspects. One group will use mobile devices while the control group will have a very similar training course, and the use of the mobile device will be a major difference. Therefore, students’ motivation in both groups should be analyzed.
Besides, interviews cannot be employed in this study. It is important to use questionnaires (as the participants’ perspectives can provide valuable insights into the way this or that intervention is perceived), but it is essential to focus on coding video recorded lessons. At that, students, as well as teachers, will be in the researchers’ lens. Thus, teachers may become weary of using mobile devices, which can affect their inclusion and rejection levels. Teachers may become less motivated in the course of time, which may translate into less effective lessons and less motivated students. The methodology used by Maulana et al. (2013) can be employed. As to students’ motivation, researchers may assess the frequency of their answers (with the focus on the correct ones), the atmosphere in the classroom, the frequency of the use of the device. Another type of data to be analyzed can be questionnaires. Teachers and students (those in the intervention group) can report about their satisfaction with the intervention as well as their motivation. As far as the students are concerned, the researchers can also check the students’ appreciation of challenge, curiosity, control, cooperation, recognition and competition.
Another significant limitation is the duration of this study. The five-month period is insufficient for drawing results. It is important to use the data obtained during a two-year longitudinal study. This period can be enough to examine the teachers’ and students’ motivation. Ciampa (2013) notes that novelties are often positively accepted, and the participants’ enthusiasm can be explained by this fact. The two-year study will eliminate this barrier. The students and teachers are unlikely to see the use of mobile devices as something new and exciting due to its novelty. Importantly, such a long research can be associated with internal validity especially as regards maturation. Clearly, students of different ages can have different views concerning the use of mobile devices. Nonetheless, the research will involve two groups that mature simultaneously, which may address (at least partially) this threat.
It is possible to note that the research concerning the use of technology can help educators employ the most efficient teaching practices and motivate students to achieve their academic goals. At that, it is quite important to provide generalizable data that could be applied in diverse settings. The use of quantitative research design, as well as a different focus and duration of the study, can address major limitations of the research under analysis.
Barkoukis, V., Taylor, I., Chanal, J., & Ntoumanis, N. (2014). The relation between student motivation and student grades in physical education: A 3-year investigation. Scandinavian Journal of Medicine & Science in Sports, 24(5), e406-e414.
Ciampa, K. (2013). Learning in a mobile age: An investigation of student motivation. Journal of Computer Assisted Learning, 30(1), 82-96.
Kiemer, K., Gröschner, A., Pehmer, A., & Seidel, T. (2015). Effects of a classroom discourse intervention on teachers’ practice and students’ motivation to learn mathematics and science. Learning and Instruction, 35, 94-103.
Maulana, R., Opdenakker, M., Stroet, K., & Bosker, R. (2013). Changes in teachers’ involvement versus rejection and links with academic motivation during the first year of secondary education: A multilevel growth curve analysis. Journal of Youth & Adolescence, 42(9), 1348-1371.
Tuominen-Soini, H., Salmela-Aro, K., & Niemivirta, M. (2012). Achievement goal orientations and academic well-being across the transition to upper secondary education. Learning and Individual Differences, 22(3), 290-305.