Introduction to Vol. 13 No. 3 (2025)

Dear Reader,

An update has been long overdue, so it gives me great pleasure to announce the publication of a new issue of Frontline Learning Research (the third of 2025). The issue comprises five articles that investigate novel methodological and empirical questions centering on data quality of surveys; emotional, motivational and cognitive aspects of learning with (different) digital tools; and math learning with an analogue, tile-based board game.

In their contribution, Donche et al. illustrate how an unobtrusive post-hoc method of CR detection can  be  applied  using  four indices, which can be calculated in most student learning surveys. By applying latent profile analyses in an  exemplary sample  of  1,111  first-year  university  students,  different responder profiles are identified, showing the  presence  of  careful  and  careless responder profiles. The study further examines the impact of CR on data quality, raising concerns about reliability and validity. The study calls for more attention to the presence of CR when analysing data in online student learning survey research. CR detection is also valuable for practice, specifically when online survey-based feedback is provided to learners with more questionable responding behaviour

Kooi et al explored how learners engage in shared control in math in Adaptive Learning Technologies  (ALT). In  shared  control,  learners  adjust  task  difficulty (easy,  medium, or hard), while the ALT selects tasks based on performance. These adjustments to task difficulty influence the probability of solving the next task correctly. This study aimed to understand(1) differences in how learners use shared control and (2) how this relates to general math ability, regulation of practice behaviour(number of finished problems and accuracy), and learning outcomes.  In  this  exploratory  study,  98  grade  5  learners practiced three  math topics using  an  ALT combined  with  an  app, including  personalised  visualisations  of learners’ real-time  progress  on  the  math  topics  and  shared  control selection  options. Results  showed  four  clusters  reflecting  differences  in  learners’use  of  shared  control  in quantity and direction of task difficulty changes: learners making no changes (cluster 1), learners  making  some  changes  preferring  hard  difficulty  (cluster  2)  or  easy  difficulty (cluster  3),and  learners  who  frequently  changed  across  all  task  difficulties  (cluster  4). Shared control was related to general math ability and influenced learners’ regulation of practice behaviour. Although a comparison with the ALT control was absent, learners seem to choose task difficulties in line with their needs and benefit from these choices, resulting in learning gain. From a self-regulated learning perspective, this indicated how learners engaged in regulation and were aware of their needs.

Henritius et al. examined students' emotional states during a virtual course at a Finnish university. The mixed methods study drew on students' experienced emotions, perceived course value, perceived control, and open-ended  descriptions  related  to  their  emotions.  The  sample  consisted  of  85  university  students.  Data  were collected at nine measurement points during a half-semester foundation course in statistics. Through latent profile analysis (LPA), we identified five distinct learner profiles described as the “Average”, “Struggling”, “Thriving”, “Victorious”, and “Determined”, and analysed how they differ based on students’ gender, form of course implementation, previous attempts at the same course, and performance. The longitudinal design revealed distinct study experiences amongst the five profiles and pinpointed that most of the challenges took place in the middle of the course. The qualitative analysis of open responses identified different explanations students gave for the changes. The multiple measurement points bring forth emotional fluctuation, which is missed if only pre-post measures are used. The multi-measurement point approach, with the identification of emotion profiles and qualitative accounts on student experiences makes a novel contribution to the field by showing how emotions fluctuate in various profiles.

Guzman-Jimenez et al. investigated the  concept  of  number that  emerges from  the  interaction of  psychological, behavioural, and  material  elements  of  numerical  cognition,  collapsing  the  distinction  between "abstract" and "concrete." This dual nature is evident in the Inca numerical system, where  tools  like  the  yupana  integrate  abstract  numerical  concepts  with  concrete materials. The  Yupana  Inka  Tawa  Pukllay  (YITP),  a  Peruvian  arithmetic  method, enhances  mathematical  and  visual-spatial  skills  through  tile-based  board  games. While  effective  with  children,  its  impact  on  university  students  is  unexplored.  This research  used  eye  tracking  to  study  gaze  and  attention  during  YITP  operations, comparing   novices   and   experts.   Eight   university   students   and   two   experts participated,  with  eye-tracking  data  and  scatter  plot  (dispersion  plot)  analyses collected using Tobii Pro Glasses. The study introduced the Variation Ratio Tokens (VRT) metric to assess visual attention efficiency, showing significant improvements in  VRT  dispersion  and  attention  during  the  arithmetic  learning  process.  These findings  suggest  YITP's  potential  in  higher  education  for  improving  cognitive processes and arithmetic performance, laying a foundation for future research and innovative educational  practices. This  work  establishes  a  foundation  for  cross-cultural cognitive studies and innovative STEM education approaches leveraging ancestral knowledge systems.

There  is  a  growing  interest  in  developing  gamified  learning  solutions  to  address educational challenges. However, learning is highly influenced by the conditions in which it takes place (e.g., does gamified learning in a laboratory setting replicate the outcomes of gamified learning online at home?).Hence, it is crucial to understand the  boundary  conditions  of  different  learning  contexts  to  effectively  implement gamified interventions that provide optimal learner support. Huber et al.’s research contributes to such an understanding by assessing how general contextual aspects of three studies on gamified  learning influence  cognitive  learning and  motivational outcomes. They examined the results of two earlier published online studies (Study 1:  n=285;  Study  2:  n=61)  and  compared  the  results  to  a  recently  conducted laboratory  study  (Study  3:  n=121),all  of  which  employed the  same  associative learning task. Comparing results through a Bayesian lens, they found that motivational outcomes induced by gamification differ substantially between contexts. In contrast, cognitive learning outcomes  seem comparatively robust across different contextual factors, with some  indication  of  subtle  influences  in  agreement  with  cognitive learning  theories. In their contribution, they discuss the implications for  future  empirical  research  on learning, highlighting how a better understanding of boundary conditions of gamified learning   interventions could open perspectives for   context-aware   educational interventions.

Kind regards,

Professor, Dr. Nina Bonderup Dohn

Editor-in-Chief, Frontline Learning Research