User Experiences from L2 Children Using a Speech Learning Application: Implications for Developing Speech Training Applications for Children
Open accessAbstract
We investigated user experiences from 117 Finnish children aged between 8 and 12 years in a trial of an English language learning programme that used automatic speech recognition (ASR). We used measures that encompassed both affective reactions and questions tapping into the children' sense of pedagogical utility. We also tested their perception of sound quality and compared reactions of game and nongame-based versions of the application. Results showed that children expressed higher affective ratings for the game compared to nongame version of the application. Children also expressed a preference to play with a friend compared to playing alone or playing within a group. They found that assessment of their speech is useful although they did not necessarily enjoy hearing their own voices. The results are discussed in terms of the implications for user interface (UI) design in speech learning applications for children.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Previous findings on Pop2TalkNordic user experiences may not generalise to the participants in the present study because they were obtained with a population of 8 to 12-year-olds using the app for second language learning.
“Although Pop2TalkNordic user experiences have been investigated before (Uther et al. 2018), this was done with a population of 8 to 12‐year‐olds who used the app for second language learning. As such, previous findings may not generalise to the participants in the present study.”
From Self‐Supervised App‐Based Speech Training for Children With Speech Sound Disorder—A Single‐Case Experimental Design Study (2026) · cites this paper as Uther et al. 2018
The Abstract and §2.1 describe a user-experience study of 117 Finnish children aged 8–12 using an English-language learning application. However, §§2.2–2.3 identify the application as SIAK, not Pop2TalkNordic, so our copy does not establish that the prior findings concerned the named app. The suggestion that those findings may not generalise is the citing authors’ inference, not a finding attributed to this source. (LLM, conf=0.84)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
A systematic literature review of empirical evidence on computer games and serious games
Connolly, T. M., Boyle, E. A., MacArthur, E., Hainey, T., & Boyle, J. M. (2012) · Computers & Education · doi:10.1016/j.compedu.2012.03.004 · Cited by 2,890 · see citing works
Technologies for foreign language learning: a review of technology types and their effectiveness
Golonka, E. M., Bowles, A. R., Frank, V. M., Richardson, D. L., & Freynik, S. (2014) · Computer Assisted Language Learning · doi:10.1080/09588221.2012.700315 · Cited by 1,144 · see citing works
Cornillie, F., Thorne, S. L., & Desmet, P. (2012) · ReCALL · doi:10.1017/s0958344012000134 · Cited by 259 · see citing works
All work and no play: Measuring fun, usability, and learning in software for children
Sim, G., MacFarlane, S., & Read, J. C. (2005) · Computers & Education · doi:10.1016/j.compedu.2005.11.021 · Cited by 146 · see citing works
On the assessment of usability testing methods for children
Markopoulos, P., & Bekker, M. M. (2003) · Interacting with Computers · doi:10.1016/s0953-5438(03)00009-2 · Cited by 119 · see citing works
Positive and negative modulation of word learning by reward anticipation
Callan, D. E., & Schweighofer, N. (2008) · Human Brain Mapping · doi:10.1002/hbm.20383 · Cited by 79 · see citing works
Cincarek, T., Gruhn, R. E., Hacker, C., Nöth, E., & Nakamura, S. (2008) · Computer Speech & Language · doi:10.1016/j.csl.2008.03.001 · Cited by 61 · see citing works
Duchateau, J., Kong, Y. O., Cleuren, L., Latacz, L., Roelens, J., Samir, A., Demuynck, K., Ghesquière, P., Verhelst, W., & hamme, H. V. (2009) · Speech Communication · doi:10.1016/j.specom.2009.04.010 · Cited by 52 · see citing works
The influence of affordances on user preferences for multimedia language learning applications
Uther, M., & Banks, A. P. (2016) · Behaviour and Information Technology · doi:10.1080/0144929x.2016.1151077 · Cited by 20 · see citing works
Self-citationDeveloping a Clearer Understanding of Genre and Mobile Gameplay
DaCosta, B., & Seok, S. (2018) · Advances in educational technologies and instructional design book series · doi:10.4018/978-1-5225-5790-6.ch008 · Cited by 1 · see citing works
Flagged first, then by citations
Research works printed but not linked: 13
- K. Reima et al., "SIAK -A Game for Foreign Language Pronunc- iation Learning, " Interspeech, vol. 2017, 2017.
- A. Rouhe, R. Karhila, K. Heini, and M. Kurimo, "A pipeline for automatic assessment of foreign language pronunciation, " ISCA Workshop on Speech and Language Technology in Education (SLaTE), vol. 2017, 2017.
- J. Mostow, S. F. Roth, A. G. Hauptmann, and M. Kane, "Pro- totype reading coach that listens, " in Proceedings of the 12th National Conference on Artificial Intelligence. Part 1 (of 2), pp. 785-792, August 1994.
- M. Black, J. Tepperman, S. Lee, P. Price, and S. Narayanan, "Automatic detection and classification of disfluent reading mis- cues in young children's speech for the purpose of assessment, " in Proceedings of the 8th Annual Conference of the International Speech Communication Association, Interspeech 2007, pp. 941- 944, Belgium, August 2007.
- D. Bolan-Os, R. A. Cole, W. Ward, E. Borts, and E. Svirsky, "FLORA: Fluent oral reading assessment of children's speech, " ACM Transactions on Speech and Language Processing, vol. 7, no. 4, 2011.
- M. Gerosa, D. Giuliani, S. Narayanan, and A. Potamianos, "A review of ASR technologies for children's speech, " in Proceedings of the 2nd Workshop on Child, Computer and Interaction, WOCCI '09, USA, November 2009.
- J. Proenc ¸a et al., "Mispronunciation Detection in Childrens Reading of Sentences, " IEEE/ACM Trans. AUDIO, vol. 26, no. 7, pp. 1203-1215, 2018.
- S. M. Abdou, S. E. Hamid, M. Rashwan et al., "Computer aided pronunciation learning system using speech recognition techniques, " in Proceedings of the INTERSPEECH 2006 and 9th International Conference on Spoken Language Processing, INTERSPEECH 2006 -ICSLP, pp. 849-852, USA, September 2006.
- F. Cornillie, S. L. Thorne, and P. Desmet, "ReCALL special issue: Digital games for language learning: Challenges and opportunities, " ReCALL, vol. 24, no. 3, pp. 243-256, 2012.
- G. Sim and M. Horton, "Investigating children's opinions of games, " in Proceedings of the the 11th International Conference, p. 70, Bremen, Germany, June 2012.
- R. Karhila, "SIAK -A game for foreign language pronunciation learning, " in Proceedings of the Annual Conference of the Interna- tional Speech Communication Association, INTERSPEECH, vol. 2017, p. 2017, 2017.
- G. Sim, J. Read, and M. Horton, "Practical and ethical concerns in usability testing with children, " in Games User Research: Study Approach, Case, A. Peters, Ed., pp. 1-33, CRC Press, 2016.
- K. Heikkinen, J. Porras, J. Read, and G. F. Welch, "Designing Mobile Applications for children, " in User Requirements for Wireless, No. September, L. T. Sorensen and and K. E. Skouby, Eds., pp. 501-512, River publishers, Aalborg, Denmark, 2015.
Cited by
Sorted by citations
The Role of Subjective Quality Judgements in User Preferences for Mobile Learning Apps
Uther, M., & Ylinen, S. (2018) · Education Sciences · doi:10.3390/educsci9010003 · Cited by 9 · see citing works
Self-citationStrömbergsson, S., Edlund, E., Pettersson, M., Phan, N., & Kurimo, M. (2026) · International Journal of Language & Communication Disorders · doi:10.1111/1460-6984.70163
“Although Pop2TalkNordic user experiences have been investigated before (Uther et al. 2018), this was done with a population of 8 to 12-year-olds who used the app for second language learning.”
Self-citationUther, M. (2019) · MDPI eBooks · doi:10.3390/books978-3-03897-661-5
Self-citation
- Authors
- Uther, M., Smolander, A.-R., Junttila, K., Kurimo, M., Karhila, R., Enarvi, S., & Ylinen, S.
- Affiliations
- University of Wolverhampton (GB)
- University of Helsinki (FI)
- Aalto University (FI)
- Corresponding author
- Uther, Maria
- Venue
- Advances in Human-Computer Interaction
- Publisher
- Wiley
- Published
- 2018-11-01
- Volume
- 2018
- Pages
- 1-6
- ISSN
- 1687-5893 (ISSN-L)
- 1687-5907
- OpenAlex
- W2899000126
- Cited by
- 3
- References
- 10
- Citations by year
- 2025: 1 · 2019: 1 · 2018: 1
- FWCI
- 0.98
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Advances in Human-Computer Interaction (publishedVersion, cc-by)
- Aaltodoc (Aalto University) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Työväentutkimus Vuosikirja (submittedVersion)
- Wolverhampton Intellectual Repository and E-Theses (University of Wolverhampton) (submittedVersion, cc-by)
- Funders
- Academy of Finland (1274058)
- Nokia Foundation (1274058)
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Educational Games and Gamification
- Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Keywords
- second language acquisition, children, speech recognition, English as a foreign language, game-based learning, user experience, affective reactions, sound quality perception, speech assessment, user interface design, peer interaction
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review