Malte Elson

Press CRTT to measure aggressive behavior: the unstandardized use of the competitive reaction time task in aggression research.

The competitive reaction time task (CRTT) is the measure of aggressive behavior most commonly used in laboratory research. However, the test has been criticized for issues in standardization because there are many different test procedures and at least 13 variants to calculate a score for aggressive behavior. We compared the different published analyses of the CRTT using data from 3 different studies to scrutinize whether it would yield the same results. The comparisons revealed large differences in significance levels and effect sizes between analysis procedures, suggesting that the unstandardized use and analysis of the CRTT have substantial impacts on the results obtained, as well as their interpretations. Based on the outcome of our comparisons, we provide suggestions on how to address some of the issues associated with the CRTT, as well as a guideline for researchers studying aggressive behavior in the laboratory.

Fight fire with rainbows

There is a large amount of variables that need to be taken into account when studying the effects of violent content in digital games; one of those being difficulty. In the current study participants played a modified first-person shooter in one of four different conditions, with either high or low difficulty and high or low violent game content. We assessed number of kills and number of deaths as game performance. Neither the difficulty nor the displayed violence had an effect on psychophysiological arousal during play, post-game aggressive cognitions, nor aggressive behavior. Thus, this study corroborates previous research indicating that violence in games does not substantially influence human behavior or experience, and other game characteristics deserve more attention in game effects studies. In addition, findings showed that challenge manipulated by game difficulty is of main importance for post-game emotions: Number of deaths predicted positive affect, but only in the low difficulty condition while number of kills was a positive predictor for positive affect and a negative predictor for negative affect. No impact of violent content on any outcome variable.No impact of game difficulty on arousal, behaviour, or affect.Difficulty slowed down cognitive processing due to exhaustion.In-game success (number of kills and deaths) was only related to post-game affect.The right amount of challenge is important for a positive game experience.

A weak scientific basis for gaming disorder: Let us err on the side of caution

We greatly appreciate the care and thought that is evident in the 10 commentaries that discuss our debate paper, the majority of which argued in favor of a formalized ICD-11 gaming disorder. We agree that there are some people whose play of video games is related to life problems. We believe that understanding this population and the nature and severity of the problems they experience should be a focus area for future research. However, moving from research construct to formal disorder requires a much stronger evidence base than we currently have. The burden of evidence and the clinical utility should be extremely high, because there is a genuine risk of abuse of diagnoses. We provide suggestions about the level of evidence that might be required: transparent and preregistered studies, a better demarcation of the subject area that includes a rationale for focusing on gaming particularly versus a more general behavioral addictions concept, the exploration of non-addiction approaches, and the unbiased exploration of clinical approaches that treat potentially underlying issues, such as depressive mood or social anxiety first. We acknowledge there could be benefits to formalizing gaming disorder, many of which were highlighted by colleagues in their commentaries, but we think they do not yet outweigh the wider societal and public health risks involved. Given the gravity of diagnostic classification and its wider societal impact, we urge our colleagues at the WHO to err on the side of caution for now and postpone the formalization.

A Unified Framework to Quantify the Credibility of Scientific Findings

Societies invest in scientific studies to better understand the world and attempt to harness such improved understanding to address pressing societal problems. Published research, however, can be useful for theory or application only if it is credible. In science, a credible finding is one that has repeatedly survived risky falsification attempts. However, state-of-the-art meta-analytic approaches cannot determine the credibility of an effect because they do not account for the extent to which each included study has survived such attempted falsification. To overcome this problem, we outline a unified framework for estimating the credibility of published research by examining four fundamental falsifiability-related dimensions: (a) transparency of the methods and data, (b) reproducibility of the results when the same data-processing and analytic decisions are reapplied, (c) robustness of the results to different data-processing and analytic decisions, and (d) replicability of the effect. This framework includes a standardized workflow in which the degree to which a finding has survived scrutiny is quantified along these four facets of credibility. The framework is demonstrated by applying it to published replications in the psychology literature. Finally, we outline a Web implementation of the framework and conclude by encouraging the community of researchers to contribute to the development and crowdsourcing of this platform.

Group Formation for Small-Group Learning: Are Heterogeneous Groups More Productive?

There is an underexploited potential in enhancing massive online learning courses through small-group learning activities. Size and diversity allow for optimizing group composition in small-group tasks. The purpose of this paper was to investigate how groups formed based on learner behavior affect productivity of students in a small-group task. Students classified as high, average and low were randomly assigned to homogeneous or heterogeneous groups. Results indicate that overall, heterogeneous groups were either similarly or a bit more productive than homogeneous groups. Yet, we found that homogeneous groups classified as high-level were as or more than heterogeneous groups. However, heterogeneous groups were still more productive than homogeneous-average and homogeneous-low groups suggesting heterogeneous groups are the best choice for the entire community. Students classified as low-level were more productive in homogeneous groups, suggesting that grouping less active students together, makes social loafing more difficult and students participate more.

Hardware reverse engineering: Overview and open challenges

Hardware reverse engineering is a universal tool for both legitimate and illegitimate purposes. On the one hand, it supports confirmation of IP infringement and detection of circuit malicious manipulations, on the other hand it provides adversaries with crucial information to plagiarize designs, infringe on IP, or implant hardware Trojans into a target circuit. Although reverse engineering is commonplace in practice, the quantification of its complexity is an unsolved problem to date since both technical and human factors have to be accounted for. A sophisticated understanding of this complexity is crucial in order to provide a reasonable threat estimation and to develop sound countermeasures, i.e. obfuscation transformations of the target circuit, to mitigate risks for the modern IC landscape. The contribution of our work is threefold: first, we systematically study the current research branches related to hardware reverse engineering ranging from decapsulation to gate-level netlist analysis. Based on our overview, we formulate several open research questions to scientifically quantify reverse engineering, including technical and human factors. Second, we survey research on problem solving and on the acquisition of expertise and discuss its potential to quantify human factors in reverse engineering. Third, we propose novel directions for future interdisciplinary research encompassing both technical and psychological perspectives that hold the promise to holistically capture the complexity of hardware reverse engineering.