The impact of educational technology: A radical reappraisal of research methods

How can we decide whether some new tool or approach is valuable? Do published results of empirical research help? This paper challenges strongly entrenched beliefs and practices in educational research and evaluation. It urges practitioners and researchers to question both results and underlying paradigms. Much published research about education and the impact of technology is pseudo‐scientific; it draws unwarranted conclusions based on conceptual blunders, inadequate design, so‐called measuring instruments that do not measure, and/or use of inappropriate statistical tests. An unacceptably high portion of empirical papers makes at least two of these errors, thus invalidating the reported conclusions

The Price Consideration Model of Brand Choice

The workhorse brand choice models in marketing are the multinomial logit (MNL) and nested multinomial logit (NMNL). These models place strong restrictions on how brand share and purchase incidence price elasticities are related. In this paper, we propose a new model of brand choice, the “price consideration” (PC) model, that allows more flexibility in this relationship. In the PC model, consumers do not observe prices in each period. Every week, a consumer decides whether to consider a category. Only then does he/she look at prices and decide whether and what to buy. Using scanner data, we show the PC model fits much better than MNL or NMNL. Simulations reveal the reason: the PC model provides a vastly superior fit to inter-purchase spells.Brand Choice; Purchase Incidence; Price Elasticity; Inter-purchase Spell

Enabling students to proactively evaluate, test and adapt the effectiveness of their learning through interactive online formative assessment

Whether we like it or not, when it comes to learning, most students are motivated by the desire to demonstrate success in the summative assessment component of the course, rather than implicitly develop their depth of knowledge, understanding and application of subject matter at hand. Viewing learning from this perspective, it is therefore vitally important to select and embed the ‘right’ assessment strategy as this will affect how and what students decide to learn, as well as how much time and effort they prioritise to different tasks and/or learning resources. In an attempt to break this cycle of assessment-driven learning, and in line with Vygotsky’s work on learning progression in which intervention allows an individual to develop further than if left on their own, a formative learning framework was developed to encourage students to take a more reflective and constructivist approach to their learning. The framework (originally funded by the Centre for Open Learning in Maths, Science, Computing and Technology CETL at The Open University), was designed to enhance student awareness, understanding and recognition of competency levels from a learning outcomes approach, and to allow them to test their ongoing academic progress at predetermined and self-selected points throughout the year. By working through each of the formative assessments, it was envisaged that students would become more self-directed and confident in their learning skills and abilities, and that this in turn would aid retention. This paper will present data collected over two-years on how students have engaged with this learning tool, the impact it has had on their perceived learning abilities and progression, the variances between expected and actual use, and the lessons learned on how formative assessment can be used as a successful method of helping students to learn how they learn, and how to do this more effectivel

Doping in Sport: A Behavioural Economics Perspective

This thesis primarily aims to provide a solid theoretical understanding behind the incentive structures, decision making and rationality of athletes who decide to utilize doping decisions within a competitive sporting contest. This thesis analyzes the rationality behind eliciting a doping decision, outline a two-stage model of doping in sport in which athletes choose how much to dope and then how much effort to exert, with payoffs determined by an all-pay auction. We also show that a winner-takes-all prize structure leads to maximum effort (when effort can be monitored) but also maximum cheating when it cannot and explore the complimentary idea that people behave more dishonestly in a sporting environment than they do in other environments through theoretical and experimental analysis

Outsourcing Memory to External Tools: A Review of 'Intention Offloading'

How do we remember delayed intentions? Three decades of research into prospective memory have provided insight into the cognitive and neural mechanisms involved in this form of memory. However, we depend on more than just our brains to remember intentions. We also use external props and tools such as calendars and diaries, strategically placed objects, and technologies such as smartphone alerts. This is known as 'intention offloading'. Despite the progress in our understanding of brain-based prospective memory, we know much less about the role of intention offloading in individuals' ability to fulfil delayed intentions. Here, we review recent research into intention offloading, with a particular focus on how individuals decide between storing intentions in internal memory versus external reminders. We also review studies investigating how intention offloading changes across the lifespan and how it relates to underlying brain mechanisms. We conclude that intention offloading is highly effective, experimentally tractable, and guided by metacognitive processes. Individuals have systematic biases in their offloading strategies that are stable over time. Evidence also suggests that individual differences and developmental changes in offloading strategies are driven at least in part by metacognitive processes. Therefore, metacognitive interventions could play an important role in promoting individuals' adaptive use of cognitive tools

Trusting in Machines: How Mode of Interaction Affects Willingness to Share Personal Information with Machines

Every day, people make decisions about whether to trust machines with their personal information, such as letting a phone track one’s location. How do people decide whether to trust a machine? In a field experiment, we tested how two modes of interaction-”expression modality, whether the person is talking or typing to a machine, and response modality, whether the machine is talking or typing back-”influence the willingness to trust a machine. Based on research that expressing oneself verbally reduces self-control compared to nonverbal expression, we predicted that talking to a machine might make people more willing to share their personal information. Based on research on the link between anthropomorphism and trust, we further predicted that machines who talked (versus texted) would seem more human-like and be trusted more. Using a popular chatterbot phone application, we randomly assigned over 300 community members to either talk or type to the phone, which either talked or typed in return. We then measured how much participants anthropomorphized the machine and their willingness to share their personal information (e.g., their location, credit card information) with it. Results revealed that talking made people more willing to share their personal information than texting, and this was robust to participants’ self-reported comfort with technology, age, gender, and conversation characteristics. But listening to the application’s voice did not affect anthropomorphism or trust compared to reading its text. We conclude by considering the theoretical and practical implications of this experiment for understanding how people trust machines

NON-NORMAL DATA IN AGRICULTURAL EXPERIMENTS

Advances in computers and modeling over the past couple of decades have greatly expanded options for analyzing non-normal data. Prior to the 1990’s, options were largely limited to analysis of variance (ANOVA), either on untransformed data or after applying a variance stabilizing transformation. With or without transformations, this approach depends heavily on the Central Limit Theorem and ANOVA’s robustness. The availability of software such as R’s lme4 package and SAS® PROC GLIMMIX changed the conversation with regard to non-normal data. With expanded options come dilemmas. We have software choices – R and SAS among many others. Models have conditional and marginal formulations. There are GLMMs, GEEs among a host of other acronyms. There are different estimation methods – linearization (e.g. pseudo-likelihood), integral approximation (e.g. quadrature) and Bayesian methods. How do we decide what to use? How much, if any, advantage is there to using GLMMs or GEEs versus more traditional ANOVA-based methods? Stroup (2013) introduced a design-to-model thought exercise called WWFD (What Would Fisher Do). This paper illustrates the use ofWWFD to clarify thinking about plausible probability processes giving rise to data in designed experiments, modeling options for analyzing non-normal data, and how to use the two evaluate small-sample behavior of competing options. Examples with binomial and count data are given. While the examples are not exhaustive, they raise issues and call into question common practice and conventional wisdom regarding non-normal data in agricultural research

Self-Esteem, Moral Capital, and Wrongdoing

We present an infinite-horizon model of moral standards where self-esteem and unconscious drives play key roles. In the model, an individual receives random temptations (such as bribe offers) and must decide which to resist. Individual actions depend both on conscious intent and a type reflecting unconscious drives. Temptations yield consumption value, but keeping a good self-image (a high belief of being the type of person that resists) yields self-esteem. We identify conditions for individuals to build an introspective reputation for goodness ("moral capital") and for good actions to lead to a stronger disposition to do good. Bad actions destroy moral capital and lock-in further wrongdoing. Economic shocks that result in higher temptations have persistent effects on wrongdoing that fade only as new generations replace the shocked cohorts. Small parametric differences across societies may lead to large wrongdoing differentials, and societies with the same moral fundamentals may display different wrongdoing rates depending on how much past luck has polarized the distribution of individual beliefs. The model illustrates how optimal deterrence may change under endogenous moral costs and how wrongdoing may be compounded as high temptation activities attract individuals with low moral capital.

How the Structure of Choices Influences Consumer Decisions and Experiences

This dissertation contains three papers that together demonstrate how the structure of a choice process and of the information consumers encounter can influence what they think, feel, and do. Chapter 1 investigates how the structure of a choice process—and in particular, the timing of a decision to act relative to the timing of the action—influences how individuals feel at the point of acting. We demonstrate that the emotional experience of guilt is composed of two dissociable sources: one tied to the decision to act, and one tied to the behavior itself. With this unpacking, we find that introducing a temporal gap between one’s decision to act and one’s behavior allows decision guilt to decay, which reduces the guilt at the point of acting and carries important behavioral consequences.Chapter 2 probes the structure of a purchasing interaction. We compare two ways that the purchase and quantity decisions in a purchase process can be organized. In one, customers make the purchase and quantity decisions separately; in the other, customers simultaneously indicate whether and how much to buy. We find that the simultaneous consideration of both choices changes the psychology of how people decide, and ultimately increases their willingness to purchase. In 27 lab experiments and a large field experiment, we find that this “quantity integration” can lead to substantial lift.Finally, chapter 3 reveals how the structure of one aspect of a customer interaction, a small monetary incentive, can influence what people believe and accordingly what they do. We show that customers who encounter a small surcharge for failing to perform some behavior infer that this behavior is more socially normative than those who encounter a small discount for performing it. This inference carries key consequences, changing how people feel and what they decide to do in the future. Collectively, these three chapters demonstrate the critical importance of the structuring of choices and information for consumers’ beliefs, emotional responses, decisions, and behaviors

Something Judicious This Way Comes...The Use of Foreshadowing as a Persuasive Device in Judicial Narrative

With the recent publication of Judge Richard Posner’s book “How Judges Think” and the nomination of Judge Sonia Sotomayer to the United States Supreme Court, there has been much discussion about the way in which judges decide cases. Although certainly an interesting (and important) discussion, what has so far gone largely ignored is the question of how judges, once they reach a decision, convince the legal audience that the decision is in fact correct. Thus, in my article, entitled Something Judicious This Way Comes . . ., I focus not on how judges think, but how they write. More specifically, I analyze the way in which judges craft their opinions so as to make them more palatable to a wide range of audience members: the litigants and attorneys involved in the case, higher appellate courts who might ultimately review the opinion, and, finally, the public in general. To do this, I focus specifically on the use of foreshadowing in legal opinions. Foreshadowing, as explained in my article, is not simply a literary device, but is an extremely persuasive technique given the way in which it appeals to how human beings think and process information. Indeed, foreshadowing implicates a number of psychological theories (priming theory, schema theory, and inoculation theory), each of which has a strong impact on persuasion. Furthermore, when we look at the general psychology behind human cognition as well as the role that subtlety (a hallmark of foreshadowing) plays in persuasion, it becomes clear why judges frequently employ foreshadowing when crafting their opinions. After discussing the above psychological theories, my article then talks specifically about judicial narrative, offering discrete examples of different kinds of foreshadowing that judges have employed in notable judicial opinions. From the way in which judges phrase rules, to how they describe precedent cases, to how they even prepare us for a departure from existing law, judicial opinions offer rich examples of the intersection between psychology, narrative and persuasion