Episodic Learner Modeling

Modeling the learner is a central aspect of intelligent tutoring systems and knowledge-based help systems that support learners in complex problem-solving domains. In this article, the episodic learner model ELM is introduced as a hybrid system that analyses novices' solutions to programming tasks based on both rule-based and case-based reasoning. ELM behaves like to a human tutor. Initially, ELM is able to analyze problem solutions based only on its domain knowledge. With increasing knowledge about a particular learner captured in a dynamic episodic case base, it adapts to the learner's individual problem-solving behavior. Two simulation studies were performed to validate the system. The first study shows that the system can learn which rules are applied successfully to diagnose code produced by programmers and that using this information reduces the computational effort of diagnoses. Using information from the episodic learner model additionally speeds up the diagnostic process. The second study shows that ELM is able to predict individual solutions. Finally, correspondences and differences to related systems are discussed.     

Stalnaker on Mathematical Information

Robert Stalnaker has argued that mathematical information is information about the sentences and expressions of mathematics. I argue that this metalinguistic account is open to a variant of Alonzo Church's translation objection and that Stalnaker's attempt to get around this objection is not successful. If correct, this tells not only against Stalnaker's account of mathematical truths, but against any metalinguistic account of truths that are both necessary and informative.     

Fit of Political Skill to the Work Context: A Two‐Study Investigation

A two‐study investigation was designed to examine the role of job type (i.e. fit of political skill to work context) as a contextual moderator of the political skill–job performance relationship. Specifically, it was hypothesised that political skill operates most effectively in enterprising job contexts, and thus is most predictive of job performance in such contexts, but political skill would demonstrate no relationship with job performance in job contexts that did not emphasise interpersonal interaction and effectiveness. In Study 1, enterprising job demands interacted with political skill to affect job performance. That is, political skill positively and significantly predicted job performance in enterprising job contexts, as hypothesised. Study 2 selected one specific job context (i.e. insurance sales) high in enterprising job demands, and hypothesised that political skill would significantly predict objective measures of insurance sales (i.e. sales volume, performance‐based income, performance‐based commission rate, and performance‐based status). The results demonstrated significant predictive effects of political skill (i.e. beyond age, sex, education level, tenure on the job, and experience in sales) on all four measures of sales performance. Contributions and implications of this research, strengths and limitations, and directions for future study are discussed.     

Detection of differential item functioning in Rasch models by boosting techniques

Methods for the identification of differential item functioning (DIF) in Rasch models are typically restricted to the case of two subgroups. A boosting algorithm is proposed that is able to handle the more general setting where DIF can be induced by several covariates at the same time. The covariates can be both continuous and (multi‐)categorical, and interactions between covariates can also be considered. The method works for a general parametric model for DIF in Rasch models. Since the boosting algorithm selects variables automatically, it is able to detect the items which induce DIF. It is demonstrated that boosting competes well with traditional methods in the case of subgroups. The method is illustrated by an extensive simulation study and an application to real data.     

Profiting from poverty

We consider whether and under what conditions it is morally illicit to profit from poverty. We argue that when profit counterfactually depends on poverty, the agent making the profit is morally obliged to relinquish it. Finally, we argue that the people to whom the profit should be redirected are those on whom it counterfactually depends.     

Overcoming procrastination: one-year follow-up and predictors of change in a randomized controlled trial of Internet-based cognitive behavior therapy

Procrastination is a common self-regulatory failure that can have a negative impact on well-being and performance. However, few clinical trials have been conducted, and no follow-up has ever been performed. The current study therefore aimed to provide evidence for the long-term benefits and investigate predictors of a positive treatment outcome among patients receiving Internet-based cognitive behavior therapy (ICBT). A total of 150 self-recruited participants were randomized to guided or unguided ICBT. Self-report measures of procrastination, depression, anxiety, and quality of life were distributed at pre-treatment assessment, post-treatment assessment, and one-year follow-up. Mixed effects models were used to investigate the long-term gains, and multiple linear regression for predictors of a positive treatment outcome, using the change score on the Irrational Procrastination Scale as the dependent variable. Intention-to-treat was implemented for all statistical analyses. Large within-group effect sizes for guided and unguided ICBT, Cohen’s d = .97–1.64, were found for self-report measures of procrastination, together with d = .56–.66 for depression and anxiety. Gains were maintained, and, in some cases, improved at follow-up. Guided and unguided ICBT did not differ from each other, mean differences ?.31–1.17, 95% CIs [?2.59–3.22], and none of the predictors were associated with a better result, bs ?1.45–1.61, 95% CIs [?3.14–4.26]. In sum, ICBT could be useful and beneficial in relation to managing procrastination, yielding great benefits up to one year after the treatment period has ended, with comparable results between guided and unguided ICBT.