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Please note that all times are shown in the time zone of the conference. The current conference time is: 17th May 2024, 04:14:37am GMT

 
 
Session Overview
Session
11 SES 11 A: Quality of Teacher Education
Time:
Thursday, 24/Aug/2023:
1:30pm - 3:00pm

Session Chair: Buratin Khampirat
Location: Sir Alexander Stone Building, 204 [Floor 2]

Capacity: 55 persons

Paper Session

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Presentations
11. Educational Improvement and Quality Assurance
Paper

Investigating the Factors Influencing Teaching Choice: an Exploratory Study with Student Teachers in a Distance Education Context

Oihana Llovet-Díaz, Patricia Gómez-Hernández, María-Mar Román-García, Raúl González-Fernández, María-Luz Cacheiro-González, Ernesto López-Gómez

UNED, Spain

Presenting Author: Llovet-Díaz, Oihana; Cacheiro-González, María-Luz

In a challenging context for the teaching profession and also for teacher education (Carrillo & Flores, 2022), it seems pertinent to highlight the relevance of teachers' motivations for choosing to teach. The factors that are sources of motivation for choosing to teach cover a wide range of nuances that are worth systematically exploring. In this regard, over the last decades, much research has been conducted on the factors that influence teaching choice in the international context (Fray and Gore, 2018; Heinz, 2015; Watt et al., 2017; Navarro et al., 2021). That is why identifying and analyzing the motivations for choosing to teach is a prolific line of research (Shang et al., 2022). Although, a scoping review of the literature shows that the investigations are contextualized in face-to-face teacher education.

From this perspective, the objective of this research is to identify the factors influencing teaching choice through an exploratory study with student teachers in a distance education context. The hypothesis that we posed is that the factors that influence the teaching choice of students in a distance university are different than those motivational profiles that traditional students have (face-to-face education) because the profile of the distance student is very heterogeneous.

Acknowledgments: Teaching Innovation Project supported by the Vicerrectorado de Digitalización e Innovación de la UNED (Spain): "Factors that influence teacher choice: an exploratory study with university students of the Degree in Early Childhood Education" (FIED-EI).


Methodology, Methods, Research Instruments or Sources Used
To address the research objective we present a quantitative, exploratory, and descriptive study. This study collected data from student teachers (teacher candidates) who completed the FIT-Choice scale (Watt & Richardson, 2007).

The research team selected the FIT-Choice scale because it is an international reference to identify the determinants of motivation for career choice, as well as the perception of the teaching profession. This is an internationally validated scale (Navarro et al. 2021) and in its Spanish version (Gratacós and López, 2016), which measures the following factors: perceived teaching abilities, intrinsic value, job security, time for family, job transferability, shape future of children, enhance social equity, make a social contribution, work with children, prior teaching and learning experiences and social influences. All these factors consisted of 50 items, and scoring was performed on a 7-point rating scale where “1” means “not important” and “7” means “very important” (Watt and Richardson, 2007; Gratacós and López, 2016).

Data collection is currently taking place (approximately 200 students will participate), through the FIT Choice scale in an online form. Research participants are previously informed about the objective of the study. Participation will be voluntary and anonymity and confidentiality will be ensured.


Conclusions, Expected Outcomes or Findings
The data obtained has been analyzed using SPSS 24.0, through descriptive techniques (mean and standard deviation) and the study of significant differences (inferential statistics) between the variables and factors. Due to it is ongoing research, recently supported by the Office of the Vice President for Innovation of our university, we cannot provide a preview of the results (the project is in the data collection phase). However, our research plan is to have the report by the end of June 2023.

The main expected result will be the identification of the most relevant motivations of teacher candidates in a distance education context, these results will be widely discussed considering previous research. The implications for the practice of a better understanding of different motivational profiles are focused on providing support and mentoring, promoting belief changes, and establishing initiatives to improve the attractiveness of the teaching profession, among others.

References
Carrillo, C., & Flores, Mª. A. (2022). Online teaching and learning practices in teacher education after COVID-19: lessons learnt from the literature. Journal of Education for Teaching, 1-13. https://doi.org/10.1080/02607476.2022.2153018

Gratacós, G. y López-Jurado, M. (2016). Validación de la versión en español de la escala de los factores que influyen en la elección de los estudios de educación (FIT-choice). Revista de Educación, 372, 87-105. https://dx.doi.org/10.4438/1988-592X-RE-2015-372-316

Fray, L., & Gore, J. (2018). Why people choose teaching: A scoping review of empirical studies, 2007–2016. Teaching and Teacher Education, 75, 153-163. https://dx.doi.org/10.1016/j.tate.2018.06.009

Heinz, M. (2015). Why choose teaching? An international review of empirical studies exploring student teachers’ career motivations and levels of commitment to teaching. Educational Research and Evaluation, 21(3), 258-297. https://dx.doi.org/10.1080/13803611.2015.1018278

Navarro, E., López, E., Asensio, I. I., Expósito, E., Carpintero, M. E., y Ruiz, C. (2021). Metaanálisis de generalización de la fiabilidad del cuestionario FIT-Choice (Factores que influyen en la elección de la enseñanza como carrera). Revista de educación, 393, 231-260. https://hdl.handle.net/11162/210363

Nocito, G., Sastre, S., Gratacós, G., & López-Gómez, E. (2022). “Conoce el atractivo de la profesión docente”: Impacto de un programa de orientación profesional dirigido a estudiantes de Bachillerato. Revista de Investigación Educativa, 40(2), 385-402.

Shang, W., Yu, T., Wang, J., Sun, D., & Su, J. (2022). Why choose to become a teacher in China? A large-sample study using the Factors Influencing Teaching Choice scale. Asia-Pacific Journal of Teacher Education, 50(4), 406-423.

Watt, H. M. G.; Richardson, P. W.; & Smith, K. (2017) Global perspectives on teacher motivation. Cambridge University Press. https://dx.doi.org/ 10.1017/9781316225202

Watt, H. M. & Richardson, P. W. (2007). Motivational factors influencing teaching as a career choice: Development and validation of the FIT-Choice scale. The Journal of experimental education, 75(3), 167-202. https://dx.doi.org/10.3200/JEXE.75.3.167-202


11. Educational Improvement and Quality Assurance
Paper

Choosing a STEM Subjects Teacher Profession: Views of Science Faculties Students

Rita Birzina, Dagnija Cedere, Jazeps Logins

University of Latvia, Latvia

Presenting Author: Birzina, Rita

The role of teachers is becoming increasingly important as Europe addresses its educational, social and economic challenges (Eurydice, 2018). At the same time, the most widespread problems in Europe and the world are teacher shortage, which is no longer a myth (Martin, & Mulvihill, 2016), but is real, large and growing, and worse than we thought (García, & Weiss, 2019). The European Commision (2015) pointed out problems of teacher shortages: shortage in some subjects, in some geographical areas, ageing teachers, high drop-out rates from the teaching profession, insufficient numbers of students in teacher studies programmes and high student attrition. The pandemic has also had an impact on the number of existing teachers, through increased anxiety and changes in workload (Darling-Hammond & Hyler 2020). The shortage of teachers, especially those for STEM (science, technology, engineering and mathematics), is a well-known global problem recognized by many (Diekman, & Benson-Greenwald, 2018).

What are the main factors influencing the teacher shortage? In this research the factors are divided into three groups: work environment/circumstances, personal and academic/professional.

Factors related to the working environment/circumstances determine a teacher's job satisfaction in school. They are: lack of recognition, poor remuneration/advancement opportunities, and loss of autonomy (Aragon 2016). Few researchers noted the characteristics of schools: type of school, class size (Cowan, et al., 2016), a perceived lack of respect for teachers (Barth,et al., 2016), and teacher workload, teacher cooperation (Toropova, Myrberg, & Johansson, 2021). In Latvia, teachers' job satisfaction is most influenced by a positive and democratic school culture - teacher relationships, teacher-student relationships and teacher-principal relationships (Geske & Ozola, 2015:206). In the LIZDAs study (2016): the biggest difficulties that teachers face in their work are the lack of respect from education policy makers, children's permissiveness, increased media interest in negative events in school life, stress and professional burnout

Personal factors are mainly related to teachers' perceptions of the teaching profession and their motivation to work in schools. Kyriacou and Coulthard’s (2000) study on undergraduates’ views of teaching as a career choice indicated three categories of the most motivating factors: altruistic reasons (desire to benefit society), intrinsic reasons (interest in subject matter and expertise), and extrinsic reasons (extended work breaks, level of pay, etc.). As the current shortage of teachers in STEM subjects calls for stimulating students' interest and motivation to learn, the teacher is given the role of inspirer. To teach, motivation can be seen as a multidimensional construct that includes (social influence, positive prior teaching and learning experiences, perceptions of teaching ability, intrinsic value, personal and social utility values), perceptions of the teaching profession (perceptions of task demands and returns), and evaluations of social withdrawal experiences and satisfaction with the teaching profession choice (Kuijpers, Dam, & Janssen, 2022).

Academic/professional factors have been attributed to the teacher's performance in the classroom: Do my knowledge, skills, and attributes fit with those demanded by the profession? (Klassen, Granger, & Bardach, 2022). It means that all teachers need the skills (explain a subject in a way that students understand, use a variety of teaching methods) and knowledge (subject content, pedagogy and psychology) to accomplish their immediate goals as a teacher.

The teacher shortage is becoming more acute today, with fewer and fewer students choosing not to become teachers. This situation is particularly problematic in STEM education, so the aim of the study was to find out the views of STEM faculties students on the choice of science teaching as a profession. In order to achieve this goal, the research question was posed: what factors determine the choice of STEM students to become/not to become a STEM subjects teacher?


Methodology, Methods, Research Instruments or Sources Used
Using the QuestionPro e-platform, 289 students (female (N = 200; male (N = 89) of Bachelor's and Master's degree programmes at the Faculties of Biology, Chemistry, Physics, Mathematics and Optometry and Geography and Earth Sciences of the University of Latvia were surveyed in 2022.  
The questionnaire was structured in two parts: general and conceptual. In the general part, closed-ended questions were used to establish the student's identity: demographic data, faculty, level of study, course of study, his/her choice of a teaching profession and expected salary. In the conceptual part, open/closed questions were used to identify students' views on the advantages, disadvantages and problems of the teaching profession. Finally, an open-ended question was asked to find out the conditions that should be fulfilled in order to study and work as a teacher.
The data obtained were processed using SPSS and AQUAD statistical data processing software. A coding system was created according to the questions of the conceptual part, which was later expanded based on the context of the open questions. Descriptive statistics, Spearman rank correlation non-parametric test, Mann-Whitney U test for two-group comparison and Chi-Square test for multiple-group comparison were used for data interpretation.

Conclusions, Expected Outcomes or Findings
The study concluded that the main factors determining the choice of a teaching profession were characterised by predominantly common socio-economic beliefs about the prestige of the teaching profession and low salaries. The main disadvantages in choosing a teacher profession are inadequate salaries (M=3.74; 94%), workload (M=3.39; 85%), limited personal growth opportunities (M=3.18; 80%) and low prestige (M=2.95; 74%).
Students consider the ability to public speak in front of an audience to be the greatest benefit of choosing teaching as a career (M=3.55; 89%). Opportunity to inspire young people (M=3.38; 85%) and ability to teach complex things simply (M=3.18; 79%) indicates students' desire to develop young people's interest in STEM subjects. It means that students were positive about the role of teachers in generating interest among young people in studying science. This is evidenced by the moderately strong correlation between the variables that are important in science (inspiring students/ability to teach complex subjects, r=0.44; ability to teach in a way that students can understand/sufficient depth and depth of subject knowledge, r=0.54). This suggests that students, few of whom have had the opportunity to be a teacher, have a reasonably good understanding of the job of a science teacher. Of the 289 students, 104 (36%) have seriously considered becoming a teacher, 14 have worked in a school, 19 are already working in a school and 89 (31%) could also teach young people in a school. Only 50 (17%) would categorically not want to work in a school.
There are no significant differences in the perceptions of students from different STEM faculties about the teaching profession. Students are able to assess the strengths and weaknesses of the teaching profession by assessing the school as a working environment, the teacher's personal perceptions and motivation to work in a school, and the teacher's professional/academic work.

References
Aragon, S. (2016). Teacher Shortages: What We Know. Teacher Shortage Series. Education Commission of the States. Denver, CO 8020
Barth, P., Dillon, N., Hull, J., & Higgins, B. H. (2016). Fixing the Holes in the Teacher Pipeline: An Overview of Teacher Shortages. Center for Public Education.
Cowan, J., Goldhaber, D., Hayes, K., & Theobald, R. (2016). Missing elements in the discussion of teacher shortages. Educational Researcher, 45(8), 460-462.
Darling-Hammond, L., & Hyler, M. E. (2020). Preparing educators for the time of COVID… and beyond. European Journal of Teacher Education, 43(4), 457-465.
Diekman, A. B., & Benson-Greenwald, T. M. (2018). Fixing STEM workforce and teacher shortages: How goal congruity can inform individuals and institutions. Policy Insights from the Behavioral and Brain Sciences, 5(1), 11-18
Eurydice. (2018). The teaching profession in Europe: Practices, perceptions, and policies. Eurydice Report. European Commission/EACEA/
European Commission. (2015). 2015 Joint Report of the Council and the Commission on the implementation of the Strategic Framework for European cooperation in education and training (ET 2020) - New priorities for European cooperation in education and training. https://eurlex.europa.eu/legalcontent/EN/TXT/?uri=CELEX:52015XG1215(02)
Geske, A., & Ozola, A. (2015). Teachers’ Job Satisfaction: Findings from TALIS 2013 Study. In Society. Integration. Education. Proceedings of the International Scientific Conference (Vol. 2, pp. 56-62).
Ingersoll, R. M. (2002). The teacher shortage: A case of wrong diagnosis and wrong prescription. NASSP bulletin, 86(631), 16-31
Kyriacou, C., & Coulthard, M. (2000). Undergraduates' views of teaching as a career choice. Journal of education for Teaching, 26(2), 117-126.
Klassen, R. M., Granger, H., & Bardach, L. (2022). Attracting prospective STEM teachers using realistic job previews: A mixed methods study. European Journal of Teacher Education, 1-23.
Kuijpers, A. J., Dam, M., & Janssen, F. J. (2022). STEM students’ career choice for teaching: studying career choice processes using personal projects. Teacher Development, 1-20.
Kunz, J., Hubbard, K., Beverly, L., Cloyd, M., & Bancroft, A. (2020). What Motivates Stem Students to Try Teacher Recruiting Programs?. Kappa Delta Pi Record, 56(4), 154-159.
LIZDA (2016). Skolotāja profesijas prestižs Latvijā. Latvijas Izglītības un zinātnes darbinieku arodbiedrība. / The prestige of the teaching profession in Latvia. Latvian Education and Science Employees' Trade Union/. https://www.lizda.lv/wp-content/uploads/2019/08/Skolotaju-prestizs.pdf
Martin, L. E., & Mulvihill, T. M. (2016). Voices in Education: Teacher Shortage: Myth or Reality?. The Teacher Educator, 51(3), 175-184.
Toropova, A., Myrberg, E., & Johansson, S. (2021). Teacher job satisfaction: the importance of school working conditions and teacher characteristics. Educational review, 73(1), 71-97.


11. Educational Improvement and Quality Assurance
Paper

Teachers' Readiness to Use Formal Performance Data to Improve Student Learning and the Impact of School Culture

Glen Molenberghs, Roos Van Gasse, Sven De Maeyer, Jan Vanhoof

Universiteit Antwerpen, Belgium

Presenting Author: Vanhoof, Jan

Background, rationale and research questions:

Although the empirical evidence on the educational impact of the systematic use of formal performance data from central tests is quite strong (Datnow & Park, 2018), the Flemish(1) education system is one of the few European education systems in which no form of central testing is widely implemented (OECD, 2013). As of school year 2023-2024, all Flemish pupils will also take central tests during their school career, which (in contrast to numerous other education systems) aim to take a strong development-oriented perspective.

While policymakers and governments expect teachers to use data to improve student learning, teachers still appear reluctant to integrate this data into their teaching practices (Schelling & Rubenstein, 2021). In this regard, a numerous number of descriptive studies provide in-depth insight into influencing factors of data use (Schildkamp, Poortman, Luyten, & Ebbeler, 2017). However, most of these studies only consider (a small number of) psychological factors to a limited extent. Since data use is essentially a human endeavour, it is important, in order to fully benefit from the rich potential of data use, to also study psychological aspects (Schildkamp, Poortman, Ebbeler, & Pieters, 2019).

Because the use of formal performance data from central tests for educational improvement can be considered a (relative) educational change, certainly in Flanders, but also to some extent in an international context, and to select psychological factors driving teachers’ data use for educational improvement, we drew inspiration from the literature related to ‘change readiness’. Armenakis, Harris and Mossholder (1993) consider teachers’ readiness as ‘one's beliefs, attitudes and goals regarding the extent to which change is needed and their perceptions of individual and organisational ability to successfully implement those changes’. The readiness to use formal performance data concerns, in other words, both ‘willing’ and 'being able' to change. Each of these dimensions explains an aspect of readiness (Rafferty, Jimmieson, & Armenakis, 2013) and is highlighted in the literature because of their role in successful educational change processes (Armenakis & Bedeian, 1999). Because readiness can be considered a predictor of behavior (Armenakis, Harris, & Mossholder, 1993), we expect that a positive teachers’ readiness (i.e. a positive appraisal of willing and being able to use formal performance data to improve student learning) may contribute to effective (future) data use. Consequently, this study firstly examines the extent to which teachers are ready to use formal performance data (from central tests) to improve student learning (RQ1).

Moreover, data use does not occur in isolation (Schildkamp et al., 2019). By including school-level factors we account for the fact that teachers’ readiness does not occur in isolation en can be impacted by a data use stimulating school culture (Prenger & Schildkamp, 2018). As a consequence we secondly study to what extent characteristics of a data use stimulating school culture have an impact on teachers’ readiness (RQ2).

In sum, the present study aims to address the aforementioned knowledge gap by quantitatively studying Flemish teachers' readiness to engage with formal achievement data (from central tests) to improve student learning and school culture’s impact.

(1) Flanders is the Dutch-speaking part of Belgium.


Methodology, Methods, Research Instruments or Sources Used
Operationalisation of concepts:

In the operationalisation of the dependent variable ‘readiness’, we have focused on the ‘will’ and ‘able’ part of this concept. The ‘will part’ of readiness was operationalised in terms of emotions or affective appraisal towards data use (Jimerson, 2014) and in terms of the usefulness of the data to improve students’ learning (Vanhoof, Vanlommel, Thijs, & Vanderlocht, 2014). The ‘able part’ of readiness was operationalised by self-efficacy (Bandura, 1997) and by teachers’ perceptions about having the necessary time for data use (Jimerson, 2016).

These central predictors of teachers’ readiness can be impacted by teachers’ perception of a data use stimulating school culture (Prenger & Schildkamp, 2018). In this study, a data use stimulating school culture was operationalised by shared goals towards data use (Vanhoof, Verhaeghe, Van Petegem, & Valcke, 2012), by internal support and collaboration in data use (Schildkamp et al., 2019), by expectations regarding data use (Vanhoof et al., 2014), by experience in the use of standardised tests, by transformational leadership (Yu, Leithwood, & Jantzi, 2002) and by level of education.

Instrument and sample:

To answer the research questions, we administered an online survey. The content in this survey was  both compiled from existing, validated scales and adopted items from previous research on data use and central tests. All items were statements to be scored on a 5-point Likert scale with a possibility to opt out. Finally, 611 Flemish teachers from 45 schools participated in the survey.

Data analysis:

To measure teachers’ individual perceptions of their readiness to engage with formal performance data to improve student learning and of a data use stimulating school culture, we constructed scales. By applying CFA, we examined the construct validity of each scale. In addition, a Cronbach's alpha was calculated for each multi-item scale as a measure of internal consistency.

Based on these scales, we applied descriptive statistics for RQ1.

In order to answer RQ2, we built and tested a path model. We started out with a model in wich shared goals, support and collaboration, expectations and use of standardised tests mediate the effect on teachers’ readiness to engage with formal performance data to improve student learning of transformational leaderschip and education level. Based on the modification indices we gradually added covariances and eliminated non-significant parameters in pursuit of a parsiminous final model with optimal fit. The path analysis was conducted in R with the lavaan-package (Rosseel, 2012).

Conclusions, Expected Outcomes or Findings
Conclusion:

Teachers’ readiness to use formal performance data to improve students’ learning can be considered an important bridge to effective data use (Armenakis et al., 1993). Yet, we found that teachers perceive only limited readiness: they have limited positive attitudes towards the use of formal performance data from central tests, they rather feel self-efficace for data use but at the same they do not perceive sufficient time to do so.

However, the path model shows that the perception of a higher level of a data use stimulating school culture has a positive impact on teachers’ readiness. In this, positive attitudes towards data use can be promoted if teachers perceive expectations regarding the use of formal performance data from central tests as clear. In addition, the can part of readiness can be promoted by perceiving supportive relationships and collaboration. This finding suggest that teachers in particular engage with data use if they perceive data use as a team event.

The many positive indirect effects of transformational leadership on teachers’ readiness we found, point to the important role of the school leader in cultivating a data use stimulating culture within school teams. Moreover, teachers' readiness to engage with formal performance data is no one-size-fits-all story. Primary school teachers appear to perceive a more stimulating data use culture, and consequently a higher degree of readiness than secondary school teachers.

By studying teachers’ readiness and promoting school-level factors, this study (further) strengthen the bridge to the use of formal performance data to improve student learning. The Flemish context with the prospect of implementing central tests charachterised by a development-oriented perspective, provided a particularly appropriate case.

References
Armenakis, A. A., & Bedeian, A. G. (1999). Organizational change: A review of theory and research in the 1990s. Journal of management, 25(3), 293-315.
Armenakis, A. A., Harris, S. G., & Mossholder, K. W. (1993). Creating readiness for organizational change. Human relations, 46(6), 681-703.
Bandura, A. (1997). Self Eflicacy. The Exercise of Control. New York: Freeman.
Datnow, A., & Park, V. (2018). Opening or closing doors for students? Equity and data use in schools. Journal of Educational Change, 19(2), 131-152.
Jimerson, J. B. (2014). Thinking about data: Exploring the development of mental models for “data use” among teachers and school leaders. Studies in Educational Evaluation, 42, 5-14.
Jimerson, J. B. (2016). How are we approaching data-informed practice? Development of the Survey of Data Use and Professional Learning. Educational Assessment Evaluation and Accountability, 28(1), 61-87. doi:10.1007/s11092-015-9222-9
OECD. (2013). Synergies for better learning. An international perspective on evaluation and assessment. Paris: OECD.
Prenger, R., & Schildkamp, K. (2018). Data-based decision making for teacher and student learning: a psychological perspective on the role of the teacher. Educational Psychology, 38(6), 734-752. doi:10.1080/01443410.2018.1426834
Rafferty, A. E., Jimmieson, N. L., & Armenakis, A. A. (2013). Change readiness: A multilevel review. Journal of management, 39(1), 110-135.
Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of statistical software, 48, 1-36.
Schelling, N., & Rubenstein, L. D. (2021). Elementary teachers’ perceptions of data-driven decision-making. Educational Assessment, Evaluation and Accountability, 33(2), 317-344.
Schildkamp, K., Poortman, C., Luyten, H., & Ebbeler, J. (2017). Factors promoting and hindering data-based decision making in schools. School Effectiveness and School Improvement, 28(2), 242-258. doi:10.1080/09243453.2016.1256901
Schildkamp, K., Poortman, C. L., Ebbeler, J., & Pieters, J. M. (2019). How school leaders can build effective data teams: Five building blocks for a new wave of data-informed decision making. Journal of Educational Change, 20(3), 283-325. doi:10.1007/s10833-019-09345-3
Vanhoof, J., Vanlommel, K., Thijs, S., & Vanderlocht, H. (2014). Data use by Flemish school principals: impact of attitude, self-efficacy and external expectations. Educational Studies, 40(1), 48-62. doi:10.1080/03055698.2013.830245
Vanhoof, J., Verhaeghe, G., Van Petegem, P., & Valcke, M. (2012). Flemish primary teachers' use of school performance feedback and the relationship with school characteristics. Educational Research, 54(4), 431-449. doi:10.1080/00131881.2012.734726
Yu, H., Leithwood, K., & Jantzi, D. (2002). The effects of transformational leadership on teachers’ commitment to change in Hong Kong. Journal of Educational Administration, 40(4), 368-389.


 
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