Adaptation of the Math-Biology Values Instrument to Preservice Teachers: German, Portuguese, and Spanish Versions

Adaptation of the Math-Biology Values Instrument to Preservice Teachers: German, Portuguese, and Spanish Versions

José María Marcos-Merino, María Rocío Esteban-Gallego, Nelson Mestrinho, Bento Cavadas, Nora Rodilla-Martín, Jesús A. G. Ochoa de Alda
DOI: 10.4018/978-1-6684-5765-8.ch013
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Abstract

Primary education curricula highlight the need for integrating STEM subjects in the classroom. Thus, preservice teachers' training programs must involve subject integration. Students' personal value to this integration is a crucial component of their motivation, influencing their outcomes. However, practitioners lack validated instruments to monitor student task-value changes to specific subject combinations. Using math in a biological context exemplifies STEM subject integration. This chapter shows the adaptation of the Math-Biology Values Instrument to preservice teachers, a tool to measure task values of using math in biology. Structural and construct validities were obtained from a sample of Spanish and an independent multicultural sample of preservice teachers, respectively. Multigroup confirmatory factor analysis supported partial measurement invariance across sexes, backgrounds, and countries. The instrument provides enough validity to monitor task-value in preservice teachers.
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Introduction

Fundamental problems of 21st-century society cannot be solved through single disciplines but require a global and integrative perspective. Current education fails to provide this perspective because, following a classical reductionist approach, educational systems are arranged into strict compartments of separate subjects (Brewer & Smith, 2011; Labov et al., 2010; McCright et al., 2013). From primary education, disciplines divide into different subjects, moving away from a global view of science (Stone, 2014). Acquiring a systemic perspective is significant for primary (elementary) education preservice teachers. If appropriately trained, they can transmit a global picture of science, technology, engineering, and mathematics (STEM) disciplines since primary education. As in other European curricula, the Spanish elementary education curriculum includes a cross-sectional block of contents for integrating natural science subjects named “Initiation to research activity,” where sciences, technology, engineering, and mathematics are fully integrated (Spanish Government, 2022). Thus, as previously noticed (Šorgo, 2010), preservice teachers' science instruction requires an interdisciplinary perspective reflecting the current science and engineering practice. Mathematics plays a pivotal role in achieving this perspective because it allows students to model, represent, and interpret experimental and observational results from various disciplines, such as biology, a science with a long descriptive tradition (May, 2004; Oltvai & Barabási, 2002). According to current educational research, integrating math into biology curricula results in increased coherence in the undergraduate biological sciences curriculum, improves quantitative skills in students, and a greater appreciation among graduates for the essential relationship between mathematics and modern biology (Thompson et al., 2013).

The barriers to establishing math-science connections in the classroom are mainly grounded in prior experiences and inadequate training. In preservice teachers, previous student experiences determine their preconceptions about teaching mathematics. They make decisions based on an external locus of control (such as the university professor, the textbook, or other sources) and harbor higher anxiety about teaching math than science (Cady & Rearden, 2007; Mellado et al., 2014; Hernández-Barco et al., 2021). Content integration is more challenging for many preservice teachers than traditional content (Leszczynski, 2014). Teacher training programs generally lack a focus on integrated teaching and do not devote time to building connections (DeLuca et al., 2015; Kim et al., 2004). As a result, preservice teachers possess weak content knowledge in both disciplines and inadequate integration models. These teachers frequently ignore fundamental differences in mathematics and science knowledge organization. Past efforts to integrate math and science reflected an insufficient understanding of negative attitudes about integration among teachers (Bursal & Paznokas, 2006; Leszczynski, 2014). This attitude, defined as the enduring tendency to evaluate this integration such as positive/negative or good/bad, can be divided into three dimensions: 1) perceived control, which includes elements such as self-efficacy (subjective perception of own capability); 2) affective states, which provides for emotions such as enjoyment and anxiety and 3) cognitive beliefs, such as perceived relevance or subjective value (Bursal & Paznokas, 2006; Buss, 2010; Cady & Rearden, 2007; Leszczynski, 2014; Riegle-Crumb et al., 2015). Subjective value is the extent to which an outcome (math-science integration in this case) is desired or valued concerning the probability of success. Psychology and neuroscience recognize this subjective value as critical to achieving motivation (Eccles & Wigfield, 2020). The subjective value of preservice teachers to math-biology integration is unexplored, mainly due to de absence of a specific, reliable, and validated instrument to monitor changes in these subjective values. The availability of this instrument would pave the way to understanding attitudes toward math-biology integration. This chapter presents the development and psychometric properties of an instrument to monitor changes in the subjective value that preservice teachers ascribe to using mathematics in biology.

Key Terms in this Chapter

Task-Value: A psychological construct that captures the student's subjective perceptions of positive (interest, utility, relevance) and negative (physical cost, intellectual cost, affective cost, economical cost) incentives to be involved in a task.

Construct Validity: Sum of pieces of evidence to support that a construct adequately represents what is intended by the theoretical framework that supported its construction.

Construct (or Psychological Constructs): A mental construction of a psychological dimension (the underlying cause of covaried human behaviors) that scales and allows understanding of behavior.

Confirmatory Factor Analysis: A statistical method used to explore the adequateness of data to a given factorial model.

Measurement Invariance: Statistical property of a construct to scale and to be measured equivalently across different groups.

Factorial Model: Representation of the variance of a set of items into two or more factors, resulting in new variables derived from the common variance groups of items.

Psychometric Instrument: A tool to measure psychological constructs such as subjective value, attitudes, or motivation.

Robust ANOVA: A tool of non-parametric statistics to explore the source of variance in the data and robust against differences in sample sizes of groups and violations of normality and homoscedasticity of variables.

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