lab.js: A free, open, online study builder

Henninger, Felix; Shevchenko, Yury; Mertens, Ulf K.; Kieslich, Pascal J.; Hilbig, Benjamin E.

doi:10.3758/s13428-019-01283-5

Cited by 126 publications

(65 citation statements)

References 37 publications

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“…In the last two decades, many interesting tools for building psychology experiments have emerged [1,[3][4][5][6]. However, these builders are either GUI-based or GPL-based.…”

Section: Discussionmentioning

confidence: 99%

“…Lab.js [4] is a browser-based, free and open-source experiment builder. Experiments can be created by writing code using a high-level JavaScript library or using an online graphical interface.…”

Section: Gui-basedmentioning

confidence: 99%

“…GUI-based experiment builders use a click/drag&drop interface to construct an experiment (e.g., OpenSesame [1], E-Prime [2], PsychoPy Builder [3], Lab.js [4], Gorilla [5]). This style is a good fit for practitioners without a programming background.…”

Section: Introductionmentioning

confidence: 99%

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PyFlies: A Domain-Specific Language for Designing Experiments in Psychology

Dejanović

Dejanović²,

Vidaković

et al. 2021

Applied Sciences

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The majority of studies in psychology are nowadays performed using computers. In the past, access to good quality software was limited, but in the last two decades things have changed and today we have an array of good and easily accessible open-source software to choose from. However, experiment builders are either GUI-centric or based on general-purpose programming languages which require programming skills. In this paper, we investigate an approach based on domain-specific languages which enables a text-based experiment development using domain-specific concepts, enabling practitioners with limited or no programming skills to develop psychology tests. To investigate our approach, we created PyFlies, a domain-specific language for designing experiments in psychology, which we present in this paper. The language is tailored for the domain of psychological studies. The aim is to capture the essence of the experiment design in a concise and highly readable textual form. The editor for the language is built as an extension for Visual Studio Code, one of the most popular programming editors today. From the experiment description, various targets can be automatically produced. In this version, we provide a code generator for the PsychoPy library while generators for other target platforms are planned. We discuss the language, its concepts, syntax, some current limitations, and development directions. We investigate the language using a case study of the implementation of the Eriksen flanker task.

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“…In the last two decades, many interesting tools for building psychology experiments have emerged [1,[3][4][5][6]. However, these builders are either GUI-based or GPL-based.…”

Section: Discussionmentioning

confidence: 99%

Section: Gui-basedmentioning

confidence: 99%

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PyFlies: A Domain-Specific Language for Designing Experiments in Psychology

Dejanović

Dejanović²,

Vidaković

et al. 2021

Applied Sciences

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“…The experiment was conducted in accordance with the ethical standards of the American Psychological Association (APA) and with the 1964 Helsinki declaration and its later amendments. The experiment was run online using lab.js (Henninger et al, 2021) and oTree (Chen et al, 2016). Participants first gave their consent and then continued to read the instructions of the task.…”

Section: Methodsmentioning

confidence: 99%

Awareness of option attractiveness increases the attraction search effect: Modeling the awareness effect in an extended iCodes model.

Scharf¹,

Glöckner²

2022

Decision

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Previous research has shown that the tendency to search information for an option increases with option attractiveness. This attraction search effect (ASE) can be explained by the integrated coherence-based decision and search (iCodes) model. In a preregistered study (N = 202), we investigated whether the ASE increases when participants are made aware of the attractiveness of an option. Participants made repeated choices between options in a task in which information was only partially accessible in a first stage and additional information could be actively searched for in a second stage. In the experimental condition, participants rated options' attractiveness between the first and the second stage, while the control group did not. The heightened awareness of option attractiveness increased the magnitude of the ASE as hypothesized and also led to increased search for information on the emerging favored option. An extended iCodes model that includes γ − a parameter tuning the relative impact of option attractiveness and the validity of information on search could account for the awareness manipulation. The iCodes model extended by the new parameter also captured reliable interindividual differences concerning the ASE and predicted the magnitude of the effect for different cue patterns. The results provide further evidence for the validity of iCodes which not only predicts the effect of attractiveness ratings but also maps the effect specifically on the theoretically adequate γ parameter. Implications for further theory development and theory integration are discussed.

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“…Moreover, we selected five true-related words (e.g., correct, proven) and five false-related words (e.g., faulty, wrong) from Nadarevic et al (2021) as stimuli for the validity-categorization trials. The procedure was similar to the previous experiments, except for the following changes: Due to the Covid-19 pandemic, we ran the experiment as a web-based study programmed with lab.js (Henninger et al, 2021). Each participant completed only one IAT.…”

Section: Design Materials and Proceduresmentioning

confidence: 99%

Color-validity associations put to the test: Examining the robustness of red-false and green-true associations in the Implicit Association Test

Nadarevic¹,

Kias²

2021

Preprint

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Although there is a considerable amount of research on color associations, not much is known about color-validity associations. Initial work with a Stroop task suggests automatic green-true and red-false associations. In the present work, we were interested in testing the generalizability of these associations by using a different procedure, the Implicit Association Test (IAT). In four IAT-experiments we investigated red-false and green-true associations across different color contexts and stimulus materials. Participants categorized objects presented in two different colors as well as true and false statements (Experiment 1), true and false mathematical equations (Experiment 2), or true-related and false-related words (Experiment 3). The hypothesized green-true and red-false associations were observed in all experiments when both red and green stimuli appeared within the same task but varied in tasks involving only one of both colors and a respective control color. The use of conceptual color representation instead of colored objects (Experiment 4) did not produce a clear pattern. A final, registered experiment aims at finding an explanation in valence- and/or salience-asymmetries as potential confounds of IAT effects.

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lab.js: A free, open, online study builder

Cited by 126 publications

References 37 publications

PyFlies: A Domain-Specific Language for Designing Experiments in Psychology

PyFlies: A Domain-Specific Language for Designing Experiments in Psychology

Awareness of option attractiveness increases the attraction search effect: Modeling the awareness effect in an extended iCodes model.

Color-validity associations put to the test: Examining the robustness of red-false and green-true associations in the Implicit Association Test

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