Helene Ackermann
Photo: SCIoI
Helene Ackermann is a psychologist with a specialization in cognitive psychology and an interest in using machine learning to better understand human cognition.
She first joined SCIoI as a research intern during her studies, supporting Project 02, then joined SCIoI as a doctoral researcher in June 2023.
Helene obtained her M.Sc. in Psychology at the University of Freiburg. Her master’s thesis focused on the application of machine learning to gain insights into the cognitive processes underlying certain eye movements.
Currently, Helene is pursuing a PhD at the University of Potsdam and SCIoI, where she is engaged in Project 50. Within this project, she investigates adaptivity in learner-teacher interactions. She’s keen on understanding how to enhance learning progress in social interactions involving artificial intelligences.
Projects
Helene Ackermann is member of:
Publications +
6984777
Ackermann
1
apa
50
date
desc
year
19779
https://www.scienceofintelligence.de/wp-content/plugins/zotpress/
%7B%22status%22%3A%22success%22%2C%22updateneeded%22%3Afalse%2C%22instance%22%3Afalse%2C%22meta%22%3A%7B%22request_last%22%3A0%2C%22request_next%22%3A0%2C%22used_cache%22%3Atrue%7D%2C%22data%22%3A%5B%7B%22key%22%3A%2222V2A7C9%22%2C%22library%22%3A%7B%22id%22%3A6984777%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Lange%20et%20al.%22%2C%22parsedDate%22%3A%222027%22%2C%22numChildren%22%3A0%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BLange%2C%20A.%20L.%2C%20Ackermann%2C%20H.%2C%20Lazarides%2C%20R.%2C%20%26amp%3B%20Hafner%2C%20V.%20V.%20%282027%29.%20A%20Robot-LLM%20Integration%20Framework%20for%20Social%20Learning%20Interactions.%20In%20O.%20Brock%2C%20J.%20Krichmar%2C%20%26amp%3B%20V.%20Mengers%20%28Eds.%29%2C%20%26lt%3Bi%26gt%3BFrom%20Animals%20to%20Animats%2018%26lt%3B%5C%2Fi%26gt%3B%20%28Vol.%2016965%2C%20pp.%20180%26%23x2013%3B191%29.%20Springer%20Nature%20Switzerland.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1007%5C%2F978-3-032-39953-3_15%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1007%5C%2F978-3-032-39953-3_15%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22bookSection%22%2C%22title%22%3A%22A%20Robot-LLM%20Integration%20Framework%20for%20Social%20Learning%20Interactions%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22editor%22%2C%22firstName%22%3A%22Oliver%22%2C%22lastName%22%3A%22Brock%22%7D%2C%7B%22creatorType%22%3A%22editor%22%2C%22firstName%22%3A%22Jeffrey%22%2C%22lastName%22%3A%22Krichmar%22%7D%2C%7B%22creatorType%22%3A%22editor%22%2C%22firstName%22%3A%22Vito%22%2C%22lastName%22%3A%22Mengers%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Anna%20L.%22%2C%22lastName%22%3A%22Lange%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Helene%22%2C%22lastName%22%3A%22Ackermann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Rebecca%22%2C%22lastName%22%3A%22Lazarides%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Verena%20V.%22%2C%22lastName%22%3A%22Hafner%22%7D%5D%2C%22abstractNote%22%3A%22%22%2C%22bookTitle%22%3A%22From%20Animals%20to%20Animats%2018%22%2C%22date%22%3A%222027%22%2C%22originalDate%22%3A%22%22%2C%22originalPublisher%22%3A%22%22%2C%22originalPlace%22%3A%22%22%2C%22format%22%3A%22%22%2C%22ISBN%22%3A%22978-3-032-39952-6%20978-3-032-39953-3%22%2C%22DOI%22%3A%2210.1007%5C%2F978-3-032-39953-3_15%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Flink.springer.com%5C%2F10.1007%5C%2F978-3-032-39953-3_15%22%2C%22ISSN%22%3A%22%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222026-10-05T08%3A28%3A55Z%22%7D%7D%2C%7B%22key%22%3A%22FCZS2ZMD%22%2C%22library%22%3A%7B%22id%22%3A6984777%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Ackermann%20et%20al.%22%2C%22parsedDate%22%3A%222026-06-12%22%2C%22numChildren%22%3A1%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BAckermann%2C%20H.%2C%20Lange%2C%20A.%20L.%2C%20Dumont%2C%20H.%2C%20Hafner%2C%20V.%20V.%2C%20%26amp%3B%20Lazarides%2C%20R.%20%282026%29.%20Real-time%20cognitive-affective%20dynamics%20of%20failure%20feedback%20in%20a%20technology-based%20learning%20task.%20%26lt%3Bi%26gt%3BCommunications%20Psychology%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B4%26lt%3B%5C%2Fi%26gt%3B%281%29%2C%2095.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1038%5C%2Fs44271-026-00487-8%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1038%5C%2Fs44271-026-00487-8%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Real-time%20cognitive-affective%20dynamics%20of%20failure%20feedback%20in%20a%20technology-based%20learning%20task%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Helene%22%2C%22lastName%22%3A%22Ackermann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Anna%20L.%22%2C%22lastName%22%3A%22Lange%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hanna%22%2C%22lastName%22%3A%22Dumont%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Verena%20V.%22%2C%22lastName%22%3A%22Hafner%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Rebecca%22%2C%22lastName%22%3A%22Lazarides%22%7D%5D%2C%22abstractNote%22%3A%22As%20technology-based%20learning%20environments%20increasingly%20employ%20automated%20feedback%2C%20understanding%20how%20learners%20process%20feedback%20in%20real%20time%20is%20essential.%20This%20study%20examined%20how%20automated%20cognitive%20and%20metacognitive%20failure%20feedback%20delivered%20by%20a%20humanoid%20robot%20affected%20performance%20and%20how%20effects%20were%20moderated%20by%20feedback%20characteristics%20and%20learner%20characteristics.%20Ninety%20adults%20%2818-59%20years%2C%20Mage%5Cu2009%3D%5Cu200929.53%2C%2061%20female%2C%2027%20male%2C%202%20diverse%29%20completed%20a%20learning%20task%20in%20three%20conditions%3A%20%281%29%20fixed%20guidance%20condition%20with%20fixed-frequency%20and%20content-generic%20feedback%2C%20%282%29%20basic-adaptive%20condition%20with%20frequency-adaptive%20but%20content-generic%20feedback%2C%20or%20%283%29%20personalized-adaptive%20condition%20with%20frequency-adaptive%20and%20content-personalized%20feedback%20adjusting%20content%20to%20learners%20specific%20errors%20and%20prior%20steps.%20A%20three-level%20generalized%20path%20model%20%28trials%20nested%20within%20time%20blocks%20within%20learners%29%20was%20estimated%20to%20investigate%20effects%20of%20failure%20feedback%20on%20immediate%20task%20performance%20and%20cross-level%20moderation%20effects.%20Results%20showed%20that%20cognitive%20and%20metacognitive%20failure%20feedback%20increased%20the%20likelihood%20of%20a%20correct%20subsequent%20response%20across%20conditions.%20Relative%20to%20fixed%20guidance%20%28condition%201%29%2C%20the%20implemented%20form%20of%20frequency-adaptive%20feedback%20%28condition%202%29%20did%20not%20show%20statistically%20significant%20moderation%20to%20these%20effects.%20Content-personalized%20feedback%20%28condition%203%29%20reduced%20effectiveness%20of%20cognitive%20failure%20feedback%20on%20immediate%20performance%20but%20improved%20overall%20performance%20as%20compared%20to%20content-generic%20feedback%20%28condition%202%29.%20Across%20conditions%2C%20learners%20with%20higher%20cognitive%20ability%20benefited%20less%2C%20while%20those%20reporting%20higher%20momentary%20on-task%20boredom%20benefited%20more%20from%20cognitive%20feedback.%20These%20findings%20highlight%20that%20the%20effectiveness%20of%20automated%20failure%20feedback%20depends%20on%20both%20its%20design%20and%20learners%5Cu2019%20situational%20cognitive%20and%20emotional%20states%2C%20illustrating%20how%20a%20situational%2C%20temporally%20sensitive%20approach%20can%20help%20open%20the%20%5Cu201cblack%20box%5Cu201d%20of%20feedback%20effectiveness.%22%2C%22date%22%3A%222026-06-12%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1038%5C%2Fs44271-026-00487-8%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.nature.com%5C%2Farticles%5C%2Fs44271-026-00487-8%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222731-9121%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222026-06-29T10%3A40%3A12Z%22%7D%7D%2C%7B%22key%22%3A%22AE3W8NX3%22%2C%22library%22%3A%7B%22id%22%3A6984777%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Ackermann%20et%20al.%22%2C%22parsedDate%22%3A%222025-02-24%22%2C%22numChildren%22%3A3%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BAckermann%2C%20H.%2C%20Lange%2C%20A.%20L.%2C%20Hafner%2C%20V.%20V.%2C%20%26amp%3B%20Lazarides%2C%20R.%20%282025%29.%20How%20adaptive%20social%20robots%20influence%20cognitive%2C%20emotional%2C%20and%20self-regulated%20learning.%20%26lt%3Bi%26gt%3BScientific%20Reports%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B15%26lt%3B%5C%2Fi%26gt%3B%281%29%2C%206581.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1038%5C%2Fs41598-025-91236-0%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1038%5C%2Fs41598-025-91236-0%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22How%20adaptive%20social%20robots%20influence%20cognitive%2C%20emotional%2C%20and%20self-regulated%20learning%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Helene%22%2C%22lastName%22%3A%22Ackermann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Anna%20L.%22%2C%22lastName%22%3A%22Lange%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Verena%20V.%22%2C%22lastName%22%3A%22Hafner%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Rebecca%22%2C%22lastName%22%3A%22Lazarides%22%7D%5D%2C%22abstractNote%22%3A%22Abstract%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20As%20educational%20environments%20become%20more%20diverse%2C%20adaptive%20technologies%20like%20social%20robots%20hold%20promise%20for%20providing%20individual%20support%20to%20learners.%20This%20study%20investigated%20the%20role%20of%20adaptive%20teaching%20of%20a%20robot%20on%20students%5Cu2019%20learning%20outcomes%2C%20emotions%2C%20and%20self-regulated%20learning%20%28SRL%29.%20A%20total%20of%20120%20participants%20%28aged%2018%5Cu201360%20years%2C%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20M%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20age%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3D%2030.25%2C%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20SD%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20age%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%3D%2010.06%2C%2064.3%25%20female%29%20engaged%20in%20an%20interactive%20vocabulary%20learning%20task%20with%20varying%20guidance%20levels%20by%20the%20robot.%20Control%20conditions%20included%20fixed%20guidance%2C%20offering%20either%20simple%20guidance%20with%20no%20hints%20%28condition%201%29%20or%20enhanced%20guidance%2C%20constantly%20adding%20hints%20%28condition%202%29.%20In%20the%20adaptive%20conditions%2C%20the%20robot%20adjusted%20the%20number%20of%20hints%20based%20on%20learners%5Cu2019%20recent%20performance%20and%20enjoyment%20%28condition%203%29%20or%20additionally%20personalized%20hints%20to%20specific%20mistakes%20%28condition%204%29.%20The%20results%20showed%20no%20direct%20or%20indirect%20effects%20of%20adaptive%20guidance%20on%20task%20performance%20or%20cognitive%20learning%20compared%20to%20fixed%20guidance.%20Instead%2C%20adaptive%20guidance%20significantly%20reduced%20on-task%20enjoyment%20compared%20to%20enhanced%20guidance%2C%20suggesting%20that%20unexpected%20variability%20in%20robot%20behavior%20may%20negatively%20affect%20emotional%20learning%20experience.%20However%2C%20personalized%20adaptive%20guidance%20increased%20certain%20SRL%20behaviors%2C%20indirectly%20benefiting%20learning%20outcomes.%20These%20findings%20highlight%20the%20need%20for%20further%20refinement%20of%20adaptive%20social%20robots%20to%20better%20meet%20individual%20learner%20needs%20and%20optimize%20outcomes.%22%2C%22date%22%3A%222025-02-24%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1038%5C%2Fs41598-025-91236-0%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.nature.com%5C%2Farticles%5C%2Fs41598-025-91236-0%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222045-2322%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222026-08-20T06%3A56%3A42Z%22%7D%7D%2C%7B%22key%22%3A%22KW8PRE6X%22%2C%22library%22%3A%7B%22id%22%3A6984777%7D%2C%22meta%22%3A%7B%22creatorSummary%22%3A%22Ackermann%20et%20al.%22%2C%22parsedDate%22%3A%222025-01-08%22%2C%22numChildren%22%3A2%7D%2C%22bib%22%3A%22%26lt%3Bdiv%20class%3D%26quot%3Bcsl-bib-body%26quot%3B%20style%3D%26quot%3Bline-height%3A%202%3B%20padding-left%3A%201em%3B%20text-indent%3A-1em%3B%26quot%3B%26gt%3B%5Cn%20%20%26lt%3Bdiv%20class%3D%26quot%3Bcsl-entry%26quot%3B%26gt%3BAckermann%2C%20H.%2C%20Henke%2C%20A.%2C%20Cheval%26%23xE8%3Bre%2C%20J.%2C%20Yun%2C%20H.%20S.%2C%20Hafner%2C%20V.%20V.%2C%20Pinkwart%2C%20N.%2C%20%26amp%3B%20Lazarides%2C%20R.%20%282025%29.%20Physical%20embodiment%20and%20anthropomorphism%20of%20AI%20tutors%20and%20their%20role%20in%20student%20enjoyment%20and%20performance.%20%26lt%3Bi%26gt%3BNpj%20Science%20of%20Learning%26lt%3B%5C%2Fi%26gt%3B%2C%20%26lt%3Bi%26gt%3B10%26lt%3B%5C%2Fi%26gt%3B%281%29%2C%201.%20%26lt%3Ba%20class%3D%26%23039%3Bzp-DOIURL%26%23039%3B%20href%3D%26%23039%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1038%5C%2Fs41539-024-00293-z%26%23039%3B%26gt%3Bhttps%3A%5C%2F%5C%2Fdoi.org%5C%2F10.1038%5C%2Fs41539-024-00293-z%26lt%3B%5C%2Fa%26gt%3B%26lt%3B%5C%2Fdiv%26gt%3B%5Cn%26lt%3B%5C%2Fdiv%26gt%3B%22%2C%22data%22%3A%7B%22itemType%22%3A%22journalArticle%22%2C%22title%22%3A%22Physical%20embodiment%20and%20anthropomorphism%20of%20AI%20tutors%20and%20their%20role%20in%20student%20enjoyment%20and%20performance%22%2C%22creators%22%3A%5B%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Helene%22%2C%22lastName%22%3A%22Ackermann%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Anja%22%2C%22lastName%22%3A%22Henke%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Johann%22%2C%22lastName%22%3A%22Cheval%5Cu00e8re%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Hae%20Seon%22%2C%22lastName%22%3A%22Yun%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Verena%20V.%22%2C%22lastName%22%3A%22Hafner%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Niels%22%2C%22lastName%22%3A%22Pinkwart%22%7D%2C%7B%22creatorType%22%3A%22author%22%2C%22firstName%22%3A%22Rebecca%22%2C%22lastName%22%3A%22Lazarides%22%7D%5D%2C%22abstractNote%22%3A%22Abstract%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20Rising%20interest%20in%20artificial%20intelligence%20in%20education%20reinforces%20the%20demand%20for%20evidence-based%20implementation.%20This%20study%20investigates%20how%20tutor%20agents%5Cu2019%20physical%20embodiment%20and%20anthropomorphism%20%28student-reported%20sociability%2C%20animacy%2C%20agency%2C%20and%20disturbance%29%20relate%20to%20affective%20%28on-task%20enjoyment%29%20and%20cognitive%20%28task%20performance%29%20learning%20within%20an%20intelligent%20tutoring%20system%20%28ITS%29.%20Data%20from%2056%20students%20%28%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20M%5Cn%20%20%20%20%20%20%20%20%20%20%20%20%20%20%5Cu2009%3D%5Cu200917.75%5Cu2009years%2C%20SD%5Cu2009%3D%5Cu20092.63%5Cu2009years%3B%2030.4%25%20female%29%2C%20working%20with%20an%20emotionally-adaptive%20version%20of%20the%20ITS%20%5Cu201cBetty%5Cu2019s%20Brain%5Cu201d%2C%20were%20analyzed.%20The%20ITS%5Cu2019%20agents%20were%20either%20depicted%20as%20on-screen%20robots%20%28condition%20A%29%20or%20as%20both%20on-screen%20avatars%20and%20physical%20robots%20%28condition%20B%29.%20Physical%20presence%20of%20the%20tutor%20agent%20was%20not%20significantly%20related%20to%20task%20performance%20or%20anthropomorphism%2C%20but%20to%20higher%20initial%20on-task%20enjoyment.%20Student-reported%20disturbance%20was%20negatively%20related%20to%20initial%20on-task%20enjoyment%2C%20and%20student-reported%20sociability%20was%20negatively%20related%20to%20task%20performance.%20While%20physical%20robots%20may%20increase%20initial%20on-task%20enjoyment%2C%20students%5Cu2019%20perception%20of%20certain%20characteristics%20may%20hinder%20learning%2C%20providing%20implications%20for%20designing%20social%20robots%20for%20education.%22%2C%22date%22%3A%222025-01-08%22%2C%22section%22%3A%22%22%2C%22partNumber%22%3A%22%22%2C%22partTitle%22%3A%22%22%2C%22DOI%22%3A%2210.1038%5C%2Fs41539-024-00293-z%22%2C%22citationKey%22%3A%22%22%2C%22url%22%3A%22https%3A%5C%2F%5C%2Fwww.nature.com%5C%2Farticles%5C%2Fs41539-024-00293-z%22%2C%22PMID%22%3A%22%22%2C%22PMCID%22%3A%22%22%2C%22ISSN%22%3A%222056-7936%22%2C%22language%22%3A%22en%22%2C%22collections%22%3A%5B%5D%2C%22dateModified%22%3A%222026-08-20T07%3A00%3A40Z%22%7D%7D%5D%7D
Lange, A. L., Ackermann, H., Lazarides, R., & Hafner, V. V. (2027). A Robot-LLM Integration Framework for Social Learning Interactions. In O. Brock, J. Krichmar, & V. Mengers (Eds.), From Animals to Animats 18 (Vol. 16965, pp. 180–191). Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-39953-3_15
Ackermann, H., Lange, A. L., Dumont, H., Hafner, V. V., & Lazarides, R. (2026). Real-time cognitive-affective dynamics of failure feedback in a technology-based learning task. Communications Psychology, 4(1), 95. https://doi.org/10.1038/s44271-026-00487-8
Ackermann, H., Lange, A. L., Hafner, V. V., & Lazarides, R. (2025). How adaptive social robots influence cognitive, emotional, and self-regulated learning. Scientific Reports, 15(1), 6581. https://doi.org/10.1038/s41598-025-91236-0
Ackermann, H., Henke, A., Chevalère, J., Yun, H. S., Hafner, V. V., Pinkwart, N., & Lazarides, R. (2025). Physical embodiment and anthropomorphism of AI tutors and their role in student enjoyment and performance. Npj Science of Learning, 10(1), 1. https://doi.org/10.1038/s41539-024-00293-z
