Removing Gamification: A Research Agenda

Abstract

The effect of removing gamification elements from interactive systems has been a long-standing question in gamification research. Early work and foundational theories raised concerns about the endurance of positive effects and the emergence of negative ones. Yet, nearly a decade later, no work to date has sought consensus on these matters. Here, I offer a rapid review on the state of the art and what is known about the impact of removing gamification. A small corpus of 8 papers published between 2012 and 2020 were found. Findings suggest a mix of positive and negative effects related to removing gamification. Significantly, insufficient reporting, methodological weaknesses, limited measures, and superficial interpretations of "negative" results prevent firm conclusions. I offer a research agenda towards better understanding the nature of gamification removal. I end with a call for empirical and theoretical work on illuminating the effects that may linger after systems are un-gamified.

Coimagining the Future of Voice Assistants with Cultural Sensitivity

“…Notably, translations of English and Japanese NLP data sets are common, such as the crowdsourcing initiatives of Tatoeba (https://tatoeba .org/en/downloads) and MASSIVE [27]. Yet, biases have been found within these data sets: "missteps" resulting from the crowdsourced translation process [55]. This suggests that translation may be insufficient.…”

“…Biases present in the data sets may be retained on translation. For instance, implicit language biases related to gender have been found in the English MASSIVE data set [59]. At present, it is unknown if these biases have been retained in the 50 translations.…”

The Usage of Voice in Sexualized Interactions with Technologies and Sexual Health Communication: An Overview

“…Extensive research has underscored both explicit and implicit biases present in algorithms and datasets, which are used to train NLP systems, concerning gender [43][44][45], race (leading to discrimination and racism, e.g., [46,47]), age (leading to ageism [48]), as well as their intersections [46,49]. The predominant focus has been on gender stereotypes, harassment, and offensive language, particularly emphasizing restricted and/or unfavorable associations with femininities and individuals identifying as genderqueer [50]. Yet, according to Seaborn and colleagues, a disparity is evident in the way the "gender problem" is conceptualized, as most of the present work is guided by a sex/gender binary model of male and female.…”

“…Yet, according to Seaborn and colleagues, a disparity is evident in the way the "gender problem" is conceptualized, as most of the present work is guided by a sex/gender binary model of male and female. Therefore, they propose a more comprehensive examination of masculine biases and gender to expose imbalances and disparities in voice assistant-oriented NLP datasets [50].…”

Interactive platforms for the teaching-learning of english as a foreign language for a student with autism spectrum disorder in high school

“…According to (Seaborn, 2021), for everything to work and take advantage of interactive platforms, it must have an accessible design, with different sensory and language processing needs. Navigation should be simple and intuitive so that students can use them independently.…”