Introducing STEM education: Implications for educating our teachers in the age of innovation

Cataloged from PDF version of article.Reforms in education of Science, Technology, Engineering, and Mathematics (STEM) disciplines have been particularly critical for the economic competitiveness of Turkey. There has been some criticism of the reforms at the teacher education level, claiming that Turkish teachers were not prepared to address the needs of their profession. The authors of this article introduced the STEM education model, which was designed with a critical investigation of the previous research on curriculum integration, STEM education, teaching knowledge, and Turkish educational reforms. By focusing on the interaction of mathematics and science, the model emphasized the importance of integrated teaching knowledge to successfully transition from the departmentalized model of teaching to an integrated model that promotes innovation

FeTeMM Eğitimi ve Alan Öğretmeni Eğitimine Yansımaları

Reforms in education of Science, Technology, Engineering, and Mathematics (STEM) disciplines have been particularly critical for the economic competitiveness of Turkey. There has been some criticism of the reforms at the teacher education level, claiming that Turkish teachers were not prepared to address the needs of their profession. The authors of this article introduced the STEM education model, which was designed with a critical investigation of the previous research on curriculum integration, STEM education, teaching knowledge, and Turkish educational reforms. By focusing on the interaction of mathematics and science, the model emphasized the importance of integrated teaching knowledge to successfully transition from the departmentalized model of teaching to an integrated model that promotes innovation.Fen, Teknoloji, Mühendislik ve Matematik (FeTeMM) ülkemizin uluslararası ölçekte rekabet gücünün korunabilmesi için stratejik öneme sahiptir. Bu alanlarda uzmanlaşacak insan gücünü yetiştirmesi beklenen öğretmenlerimizin çağın gereklerine uygun şekilde eğitilmedikleri konusunda yoğun eleştiriler vardır. Bu makale ile FeTeMM eğitiminin kuramsal bir çerçeve etrafında tanıtılması amaçlanmıştır. Bu amaca yönelik olarak bütünleşik müfredat ve öğretmenlik bilgisi alanlarında ülkemizde ve dünyada yapılmış araştırmalar ile süregelen eğitim reform girişimleri incelenmiştir. Kavramlaştırılan modelin bir çıktısı olan fen ve matematik arasındaki etkileşime yoğunlaşıldığında, öğretmenlerimizin sadece uzman oldukları alanda öğretmenlik bilgisine sahip olmalarının ülkemizin ihtiyacı olan insan gücünü yetiştirmede yeterli olmayacağı sonucuna varılmıştır

Mathematical foundations of moral preferences

One-shot anonymous unselfishness in economic games is commonly explained by social preferences, which assume that people care about the monetary payoffs of others. However, during the last ten years, research has shown that different types of unselfish behaviour, including cooperation, altruism, truth-telling, altruistic punishment, and trustworthiness are in fact better explained by preferences for following one’s own personal norms – internal standards about what is right or wrong in a given situation. Beyond better organ- ising various forms of unselfish behaviour, this moral preference hypothesis has recently also been used to increase charitable donations, simply by means of interventions that make the morality of an action salient. Here we review experimental and theoretical work dedicated to this rapidly growing field of research, and in doing so we outline mathematical foundations for moral preferences that can be used in future models to better understand selfless human actions and to adjust policies accordingly. These foundations can also be used by artificial intelligence to better navigate the complex landscape of human morality

A longitudinal study of the relationship between mathematics and science: The case of Texas

Cataloged from PDF version of article.This study aims to investigate the relationship between mathematics and science scores acquired from the Texas Assessment of Knowledge and Skills (TAKS) examination, and how this relationship changed over the years. The participants were from an independent school district in a northern Texas town. Criterion sampling was used in this study to assure that students who were selected had four TAKS mathematics scores from 2006 through 2010 and two TAKS science scores for 2006 and 2010: 116 students met the criteria. The relationship between two subjects was investigated by analyzing the correlation between students’ mathematics and science scores of 2006 and 2010. Growth curve models were used to reveal whether there was growth on students’ mathematics and science scores over the years. A strong correlation was found between mean mathematics and mean science scores in the whole sample, and a greater growth was found in mathematics than it did for science

Lying on networks: the role of structure and topology in promoting honesty

Lies can have a negating impact on governments, companies, and the society as a whole. Understanding the dynamics of lying is therefore of crucial importance across different fields of research. While lying has been studied before in well-mixed populations, it is a fact that real interactions are rarely well-mixed. Indeed, they are usually structured and thus best described by networks. Here we therefore use the Monte Carlo method to study the evolution of lying in the sender-receiver game in a one-parameter family of networks, systematically covering complete networks, small-world networks, and one-dimensional rings. We show that lies which benefit the sender at a cost to the receiver, the so-called black lies, are less likely to proliferate on networks than they do in well-mixed populations. Honesty is thus more likely to evolve, but only when the benefit for the sender is smaller than the cost for the receiver. Moreover, this effect is particularly strong in small-world networks, but less so in the one-dimensional ring. For lies that favor the receiver at a cost to the sender, the so-called altruistic white lies, we show that honesty is also more likely to evolve than it is in well-mixed populations. But contrary to black lies, this effect is more expressed in the one-dimensional ring, whereas in small-world networks it is present only when the cost to the sender is greater than the benefit for the receiver. Lastly, for lies that benefit both the sender and the receiver, the so-called Pareto white lies, we show that the network structure actually favors the evolution of lying, but this only when the benefit for the sender is slightly greater than the benefit for the receiver. In this case again the small-world topology acts as an amplifier of the effect, while other network topologies fail to do the same. In addition to these main results we discuss several other findings, which together show clearly that the structure of interactions and the overall topology of the network critically determine the dynamics of lying

Group size effects and critical mass in public goods games

Understanding whether the size of the interacting group has an effect on cooperative behavior has been a major topic of debate since the seminal works on cooperation in the 1960s. Half a century later, scholars have yet to reach a consensus, with some arguing that cooperation is harder in larger groups, while others that cooperation is easier in larger groups, and yet others that cooperation attains its maximum in intermediate size groups. Here we add to this field of work by reporting a two-treatment empirical study where subjects play a Public Goods Game with a Critical Mass, such that the return for full cooperation increases linearly for early contributions and then stabilizes after a critical mass is reached (the two treatments differ only on the critical mass). We choose this game for two reasons: it has been argued that it approximates real-life social dilemmas; previous work suggests that, in this case, group size might have an inverted-U effect on cooperation, where the pick of cooperation is reached around the critical mass. Our main innovation with respect to previous experiments is that we implement a within-subject design, such that the same subject plays in groups of different size (from 5 to 40 subjects). Groups are formed at random at every round and there is no feedback. This allows us to explore if and how subjects change their choice as a function of the size of the group. We report three main results, which partially contrast what has been suggested by previous work: in our setting (i) the critical mass has no effect on cooperation; (ii) group size has a positive effect on cooperation; (iii) the most chosen option (played by about 50% of the subjects) is All Defection, followed by All Cooperation (about 10% of the subjects), whereas the rest have a slight trend to switch preferentially from defection to cooperation as the group size increases

Author correction: Group size effects and critical mass in public goods games

An amendment to this paper has been published and can be accessed via a link at the top of the paper

From outcome-based to language-based preferences

We review the literature on models that try to explain human behavior in social interactions described by normal-form games with monetary payoffs. We start by covering social and moral preferences. We then focus on the growing body of research showing that people react to the language in which actions are described, especially when it activates moral concerns. We conclude by arguing that behavioral economics is in the midst of a paradigm shift towards language-based preferences, which will require an exploration of new models and experimental setups

The evolution of lying in well-mixed populations

Lies can have profoundly negative consequences for individuals, groups and even for societies. Understanding how lying evolves and when it proliferates is therefore of significant importance for our personal and societal well-being. To that effect, we here study the sender–receiver game in well-mixed populations with methods of statistical physics. We use the Monte Carlo method to determine the stationary frequencies of liars and believers for four different lie types. We consider altruistic white lies that favour the receiver at a cost to the sender, black lies that favour the sender at a cost to the receiver, spiteful lies that harm both the sender and the receiver, and Pareto white lies that favour both the sender and the receiver. We find that spiteful lies give rise to trivial behaviour, where senders quickly learn that their best strategy is to send a truthful message, while receivers likewise quickly learn that their best strategy is to believe the sender’s message. For altruistic white lies and black lies, we find that most senders lie while most receivers do not believe the sender’s message, but the exact frequencies of liars and non-believers depend significantly on the payoffs, and they also evolve non-monotonically before reaching the stationary state. Lastly, for Pareto white lies we observe the most complex dynamics, with the possibility of both lying and believing evolving with all frequencies between 0 and 1 in dependence on the payoffs. We discuss the implications of these results for moral behaviour in human experiments

The evolution of trust and trustworthiness

Trust and trustworthiness form the basis for continued social and economic interactions, and they are also fundamental for cooperation, fairness, honesty, and indeed for many other forms of prosocial and moral behaviour. However, trust entails risks, and building a trustworthy reputation requires effort. So how did trust and trustworthiness evolve, and under which conditions do they thrive? To find answers, we operationalize trust and trustworthiness using the trust game with the trustor’s investment and the trustee’s return of the investment as the two key parameters. We study this game on different networks, including the complete network, random and scale-free networks, and in the well-mixed limit. We show that in all but one case, the network structure has little effect on the evolution of trust and trustworthiness. Specifically, for well-mixed populations, lattices, random and scale-free networks, we find that trust never evolves, while trustworthiness evolves with some probability depending on the game parameters and the updating dynamics. Only for the scale-free network with degree non-normalized dynamics, we find parameter values for which trust evolves but trustworthiness does not, as well as values for which both trust and trustworthiness evolve. We conclude with a discussion about mechanisms that could lead to the evolution of trust and outline directions for future work