Cited by 39Intelligent Tutoring Systems and Adaptive LearningArtificial Intelligence in EducationAI in Service Interactions

Using ChatGPT is easy, using it effectively is tough? A mixed methods study on K-12 students’ perceptions, interaction patterns, and support for learning with generative AI chatbots

Open access
Klar, Maria·2025·Smart Learning Environments

Abstract

Generative AI (genAI) chatbots can be a powerful tool for learning, especially self-regulated learning, but they can also add more complexity to the learning process because of their numerous capabilities. Learners might not make use of these capabilities and fail to profit from them. One core genAI affordance is to adapt any learning material to the learner’s individual needs. To help learners make use of these adaptation capabilities, instructional prompts can help, but they can also have negative effects on cognitive load. This study investigated K-12 learners’ perceptions and interaction patterns with a chatbot, focusing on their use of content adaptation capabilities. In this experimental study with 106 secondary school students, a group receiving adaptation guidance (including brief instruction, prompt suggestions, and adjustable chatbot response length and language level) was compared to a control group without adaptation guidance. Results show that learners perceived chatbots as easy to use despite limited prior experience. Without guidance, they underutilized the chatbot’s adaptation capabilities. The experimental group used twice as many adaptation prompts (M = 6.0) compared to the control group (M = 2.5), without experiencing increased cognitive load. Interestingly, both groups showed similar knowledge gains and reported high satisfaction levels. These findings suggest that easily implementable interventions can enhance students’ use of genAI chatbot capabilities, potentially improving their self-regulated learning experiences. Future research should explore the long-term effects of adaptation guidance on learning outcomes and self-regulated learning skills.

AI snapshot

Written from the paper’s full text.

TL;DR

This mixed-methods experiment with 106 German 9th–10th graders found that K-12 students perceived a generative AI chatbot as easy to use and were highly satisfied, but without guidance they underused its adaptation capabilities. Brief adaptation guidance doubled adaptation-prompt use without increasing extraneous load or improving knowledge gains.

Key findings

  • Learners rated the chatbot favorably in both conditions: ease of use was high (control M = 6.47; experimental M = 6.53) and overall satisfaction was high (control M = 6.17; experimental M = 6.25), despite limited prior chatbot experience.
  • Adaptation guidance significantly increased adaptation prompts: experimental group M = 6.0 vs. control M = 2.51, F(1, 104) = 41.085, p < .001, partial η² = 0.283. One third of control students used no adaptation prompt, while all experimental students used at least one.
  • There were no significant group differences in extraneous load (experimental M = 3.0 vs. control M = 2.77, p = .349) or knowledge gain (experimental M = 2.43 vs. control M = 2.52, p = .654).
  • Interaction patterns differed: the experimental group asked more questions overall (M = 7.8 vs. 4.8, p < .001) and more follow-up questions (M = 1.4 vs. 0.8), and engaged in less off-topic conversation; 83% used at least one suggested prompt, but only 27% used the buttons to change response length or language level.

Methods

  • Experimental, value-added design with 106 secondary school students (grades 9–10) in Germany, recruited from five schools and randomly assigned by small group to experimental or control condition.
  • Both groups conducted 20 minutes of exploratory research on “cognitive biases” using a ChatGPT-3.5-based chatbot; the experimental group received adaptation guidance consisting of a 2.5-minute instruction on adaptation prompts, follow-up prompt suggestions, and options to adjust response length and language level.
  • Quantitative analysis used MANOVA and post-hoc univariate ANOVAs, plus PROCESS moderation analyses for prior knowledge, chatbot experience, and self-regulated learning skills; qualitative chat protocols were coded for interaction patterns with weighted kappa for adaptation prompts (κ = 0.94) and questions (κ = 0.91).

Limitations

  • Stated: possible demand characteristics from the instructional pointers may have affected extraneous load, because control students may not have perceived the task as requiring adaptation and thus had little extraneous load to reduce.
  • Stated: ecological validity was limited because students could not use web search and were restricted to the chatbot; the single 20-minute interaction limits conclusions about long-term effects, and the sample was not large enough to detect small effects.
  • Evident from the text: the SRL subscale had low reliability (Cronbach’s α = 0.60), and prior domain knowledge and chatbot experience were low with little variance, which the paper notes may explain the lack of moderation effects.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1186/s40561-025-00385-2

Cites

47 of 47 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

0 of 17 cited sources checked · 0 supported · 0 flagged

  • Findingown data

    Without adaptation guidance, learners underutilized the chatbot's adaptation capabilities.

    “Without guidance, they underutilized the chatbot's adaptation capabilities.”
    Quote in the paperSubstantial claim
  • Findingown data

    Learners perceived the chatbot as easy to use despite limited prior experience.

    “Results show that learners perceived chatbots as easy to use despite limited prior experience.”
    Quote in the paperNot a substantial claim
  • Findingown data

    15% of learners in the experimental group and 23% in the control group engaged in off-topic chat at least once.

    “15% (8) of the learners in the experimental group and 23% (12) in the control group engaged in off-topic chat at least once.”
    Quote in the paperNot a substantial claim
  • Findingreasoning

    If one removed all user inputs and appended all chatbot outputs from a single user session, many if not most of the chatbot outputs could be characterized as an encyclopedic article.

    “If one removed all the user inputs and appended all the chatbot outputs from a single user session, many if not most of the chatbot outputs could be characterized as an encyclopedic article.”
    Quote in the paperSubstantial claim
  • Findingown data

    Overall, both groups showed an interaction style that could be likened to generating an (adapted) encyclopedic article on the topic.

    “Overall, both groups showed an interaction style that could be likened to generating an (adapted) encyclopedic article on the topic.”
    Quote in the paperNot a substantial claim
  • May combine two claims. 45
  • The quote only partly states this claim. 3
  • Classified as probably not a substantial claim. 24
  • May combine two claims.

    Findingreasoning

    Participants' requests were usually fulfilled by the chatbot, so they usually experienced the interaction as successful.

    “The participants' requests were usually fulfilled by the chatbot, so they usually experienced the interaction as successful.”
    Quote in the paperSubstantial claim
  • May combine two claims.

    Findingown data

    Participants in the experimental group asked for an outline or had the chatbot make a table, which was not asked in the control group.

    “For example, participants in the EG asked for an outline or had the chatbot make a table, which was not asked in the control group.”
    Quote in the paperNot a substantial claim
  • May combine two claims. The quote only partly states this claim.

    Findingown data

    Adaptation guidance did not increase extraneous cognitive load; there was no significant difference between groups.

    “without experiencing increased cognitive load”
    • Also stated in: § RQ3 and RQ4: hypothesis tests · plain
      “Learners report similar levels of extraneous load in the experimental group (M = 3.0) and in the control group (M = 2.77).”
    Quote in the paperSubstantial claim
  • May combine two claims.

    Findingown data

    The experimental group used more prompts overall, especially more follow-up questions and adaptation prompts, while the control group showed more off-topic conversation.

    “The experimental group used more prompts overall, especially more follow-up questions and adaptation prompts, while the control group showed more off-topic conversation which signals a difference in engagement between the two groups.”
    Quote in the paperSubstantial claim
  • May combine two claims.

    Findingown data

    Many chatbot interactions were a series of questions covering general aspects of the topic, with a few adaptation prompts in most conversations and single follow-up questions in many.

    “Many chatbot interactions were a series of questions covering the general aspects of the topic (i.e., explanation, examples, causes, consequences, and remedies of cognitive biases), with a few adaptation prompts in most conversations and single follow-up questions in many.”
    Quote in the paperSubstantial claim
  • May combine two claims.

    Findingown data

    Overall, the experimental group had more interactions with the chatbot and less off-topic conversation.

    “Overall, they had more interactions with the chatbot and less offtopic conversation.”
    Quote in the paperNot a substantial claim
  • May combine two claims.

    Findingown data

    There is no significant difference between the conditions regarding several items on satisfaction, despite differences in use of adaptation prompts.

    “Second, despite differences in use of adaptation prompts, there is no significant difference regarding several items on satisfaction.”
    Quote in the paperSubstantial claim
  • May combine two claims.

    Findingcitation

    Complex, interactive SRL learning activities, as suggested by Chiu (2024), are not present in the control group and to some extent in the group with adaptation guidance.

    “Complex, interactive SRL learning activities, as suggested by Chiu (2024), are not present in the control group and to some extent in the group with adaptation guidance.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Chiu (2024) source

      Not checked in the free run.

  • May combine two claims.

    Findingown data

    On average, participants did not prompt the chatbot as if it was a search engine, but they did not engage with it like a human interlocutor either.

    “In terms of overall interaction style, it is notable that, on average, the participants did not prompt the chatbot as if it was a search engine (i.e., with abstracted search terms), but they did not engage with it like a human interlocutor either.”
    Quote in the paperSubstantial claim
  • May combine two claims.

    Findingown data

    The experimental group used more follow-up questions and more general questions when self-written questions and suggested questions were added up.

    “The experimental group used more follow-up questions and more general questions when self-written questions and suggested questions were added up for the EG.”
    Quote in the paperSubstantial claim
  • May combine two claims.

    Findingown data

    18% of the adaptation prompts and 19% of the questions prompted by the students were suggested by the chatbot.

    “18% of the adaptation prompts and 19% of the questions prompted by the students were suggested by the chatbot, so this feature was used considerably often but students also did not overly rely on it.”
    Quote in the paperSubstantial claim
  • May combine two claims.

    Findingown data

    In both groups, students felt they always knew what to ask next and that they always received the response they needed.

    “In both groups, students felt they always knew what to ask next (CG: M = 4.4; EG: M = 4.57) and that they always received the response they needed (CG: M = 5.16; EG: M = 5.17).”
    Quote in the paperNot a substantial claim
  • The quote only partly states this claim.

    Findingown data

    Knowledge gain did not differ significantly between the experimental and control groups.

    “both groups showed similar knowledge gains”
    • Also stated in: § RQ3 and RQ4: hypothesis tests · plain
      “The mean difference between pre-and post-test scores is similar between the experimental group (M = 2.43) and the control group (M = 2.52).”
    Quote in the paperSubstantial claim
  • May combine two claims.

    Findingown data

    Descriptively, the experimental group rated their germane load as higher (M = 5.2) than the control group (M = 4.9), but the difference is not significant.

    “However, this interpretation is not clearly reflected in the ratings of germane load: Descriptively, the EG rated their germane load as higher (M = 5.2) than the control group (M = 4.9), but the difference is not significant.”
    Quote in the paperNot a substantial claim
  • May combine two claims.

    Findingown data

    Students judged their ability to use chatbots for learning as high, despite using them only a few times a month and having had teacher instruction on chatbots only once.

    “First, students judged their ability to use chatbots for learning as high, even though they used them only a few times a month and they had had teacher instruction on chatbots only once.”
    Quote in the paperSubstantial claim
  • May combine two claims.

    Findingown data

    There were no moderation effects found for domain knowledge, chatbot experience, or SRL skills.

    “There were no moderation effects found for either of these aspects.”
    Quote in the paperSubstantial claim
  • May combine two claims.

    Findingown data

    Irrespective of the level of prior knowledge on domain knowledge, chatbot experience, and SRL skills, students used significantly more adaptation prompts and did not differ significantly in terms of learning gains and extraneous load.

    “That is, irrespective of the level of prior knowledge on these three aspects, the students used significantly more adaptation prompts and did not differ significantly in terms of learning gains and extraneous load.”
    Quote in the paperSubstantial claim
  • May combine two claims.

    Findingown data

    Students generally perceived the chatbots favorably and reported high levels of satisfaction and ease of use, regardless of whether they received adaptation guidance.

    “First, students generally perceived the chatbots favorably and reported high levels of satisfaction and ease of use, regardless of whether they received adaptation guidance.”
    Quote in the paperSubstantial claim
  • May combine two claims.

    Findingown data

    The automatically generated prompt suggestions were used, but not overused, and were perceived as useful.

    “More specifically, the automatically generated prompt suggestions were used, but not overused, and were perceived as useful.”
    Quote in the paperSubstantial claim
  • May combine two claims.

    Findingown data

    Students who received adaptation guidance used a greater variety and a significantly higher number of adaptation prompts, asked more follow-up questions, and engaged in less off-topic conversation.

    “Students who received adaptation guidance used a greater variety and a significantly higher number of adaptation prompts, asked more follow-up questions, and engaged in less off-topic conversation.”
    Quote in the paperSubstantial claim
  • May combine two claims.

    Findingown data

    Prior domain knowledge and prior chatbot experience were low overall and showed little variance, which was possibly a reason for the lack of moderation effect.

    “Prior domain knowledge and prior chatbot experience were low overall and showed little variance, which was possibly a reason for the lack of moderation effect.”
    Quote in the paperSubstantial claim
  • May combine two claims.

    Interpretationown data

    Hypotheses 4.1 through 4.3 are not supported by the data for extraneous load and knowledge gain and could not be tested for adaptation prompts.

    “Therefore, hypotheses 4.1 through 4.3 are not supported by the data for extraneous load and knowledge gain and could not be tested for adaptation prompts.”
    Quote in the paperSubstantial claim
  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Tasks requiring the learner to search among multiple solutions induce extraneous load.

    “Tasks requiring the learner to search among multiple solutions induce extraneous load, i.e., load induced by processing information that is irrelevant to the task (Sweller, 2011).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Sweller, 2011

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationcitation

    Students need tailored support to effectively use chatbots for self-regulated learning.

    “Abdelhalim (2024) found that students with high metacognitive awareness used ChatGPT more skillfully for research than those with lower awareness, suggesting students need tailored support to effectively use chatbots for self-regulated learning.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Abdelhalim, 2024 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S4 (based). May combine two claims.

    Interpretationcitation

    Learners perceive chatbots as easy to use, which is an indication that they underutilize beneficial capabilities and possibly invest too little mental effort.

    “The fact that learners perceive chatbots as easy to use is an indication that they underutilize these beneficial capabilities and possibly also invest too little mental effort.”
    Quote in the paperNot a substantial claim
  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Interpretationreasoning

    Deciding among adaptation options can induce cognitive load.

    “Deciding among these adaptation options can induce cognitive load.”
    Quote in the paperNot a substantial claim
  • May combine two claims.

    Interpretationown data

    Given that students in the experimental group had only received a very short instruction on adaptation prompts and prompt suggestions, this small intervention produced a large effect.

    “Conversely, given that the students in the experimental group had only received a very short instruction on adaptation prompts and prompt suggestions, this small intervention produced a large effect.”
    Quote in the paperSubstantial claim
  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.

    Interpretationreasoning

    Changing the overall length to shorter and the language to simple might have been undesirable for students because it would reflect badly on their performance, and because students might have felt they missed out on important information.

    “Changing the overall length to”
    Quote in the paperNot a substantial claim
  • May combine two claims.

    Interpretationown data

    Even though students reported high confidence in their skill to effectively use chatbots for learning, they do not make use of the basic capabilities when unassisted.

    “This indicates that even though the students reported high confidence in their skill to effectively use chatbots for learning, they do not make use of the basic capabilities when unassisted.”
    Quote in the paperSubstantial claim
  • May combine two claims.

    Interpretationcitation

    The larger number of adaptations might have benefitted one aspect of learning but impaired another.

    “The larger number of adaptations might have benefitted one aspect of learning but impaired another: Berthold et al. (2011) found evidence that explanation prompts can be double-edged in that they increase conceptual knowledge and detailedness of explanations, while they reduce procedural knowledge and number of tasks performed.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Berthold et al. (2011) source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    106 of the 108 datasets were complete and included in the sample.

    “106 of the 108 datasets were complete and included in the sample.”
    Quote in the paperNot a substantial claim
  • May combine two claims.

    Interpretationown data

    Easily implementable interventions can enhance students' use of genAI chatbot capabilities, potentially improving their self-regulated learning experiences.

    “These findings suggest that easily implementable interventions can enhance students' use of genAI chatbot capabilities, potentially improving their self-regulated learning experiences.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: Using more adaptation prompts improves students' self-regulated learning.
    • Rests on an assumption: The adaptation guidance intervention is easily implementable in real educational settings.
  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductown data

    The second rater coded all chats with the coding scheme, and intercoder agreement was weighted kappa κ = 0.94 for adaptation prompts and κ = 0.91 for questions.

    “The second rater coded all chats with this coding scheme.In cases of a discrepancy greater than 1, both raters discussed the case and reached an agreement.The intercoder agreement was then calculated as the weighted kappa for adaptation prompts (κ = 0.94) and questions (κ = 0.91).”
    Quote in the paperSubstantial claim
  • Classified as probably not a substantial claim.

    Study design and conductown data

    Knowledge was assessed through open-ended pre-and post-tests scored by two raters with interrater agreement κ = 0.70-0.79 for pre-test and κ = 0.74-0.88 for post-test.

    “Knowledge was assessed through open-ended pre-and post-tests on cognitive biases, scored for breadth, depth, and precision by two raters.”
    • Also stated in: § Instruments · plain
      “interrater agreement reached κ = 0.70 for breadth, κ = 0.73 for depth and κ = 0.79 for precision for the pre-test, and κ = 0.88 for breadth, κ = 0.83 for depth and κ = 0.74 for precision for the post-test.”
    Quote in the paperSubstantial claim
  • May combine two claims.

    Interpretationown data

    Extensive 'prompt training' might not be necessary, but targeted, short instruction prior to a task can be effective.

    “This shows that extensive”
    Quote in the paperSubstantial claim
  • May combine two claims.

    Interpretationreasoning

    In addition to being supportive, the instruction, and maybe also the supportive interface features, raised the task difficulty: Students in the control group did not perceive the task demand of adapting the chatbot responses to their needs.

    “In addition to being supportive, the instruction, and maybe also the supportive interface features, raised the task difficulty: Students in the control group did not perceive the task demand of adapting the chatbot responses to their needs.”
    Quote in the paperNot a substantial claim
  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    Self-regulated learning can cause cognitive load due to constant decision-making.

    “From this perspective, self-regulated learning can cause cognitive load due to constant decision-making.”
    Quote in the paperNot a substantial claim
  • May combine two claims.

    Interpretationreasoning

    Because students did not perceive the versatility the chatbot affords, they had a smaller range of possible next prompts and were not overwhelmed by the plentitude of interaction possibilities.

    “Because the students did not perceive the versatility the chatbot affords, they had a smaller range of possible next prompts and were not overwhelmed by the plentitude of interaction possibilities.”
    Quote in the paperSubstantial claim
  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Interpretationreasoning

    There are aspects of chatbots that can increase cognitive load, such as the numerous indirect affordances and lack of SRL support, while others, like the intuitive interface, may reduce it.

    “Therefore, there are aspects of chatbots that can increase cognitive load, such as the numerous indirect affordances and lack of SRL support, while others, like the intuitive interface, may reduce it.”
    Quote in the paperNot a substantial claim
  • May combine two claims.

    Interpretationreasoning

    The experimental group was more engaged in the task and the conversation with the chatbot.

    “This suggests that the experimental group was more engaged in the task and the conversation with the chatbot.”
    Quote in the paperNot a substantial claim
  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductreasoning

    This study can be considered a true experimental study despite group-level randomization.

    “On average, there were four students per group, so while randomization did not take place at the individual level but at the level of a small group, this study can be considered a true experimental study in contrast to quasi-experimental studies where whole classes are randomized.”
    Quote in the paperNot a substantial claim
  • Classified as probably not a substantial claim.

    Study design and conductcitation

    Cognitive load was assessed using the 8-item instrument by Klepsch et al. (2017).

    “Cognitive load was assessed using the 8-item instrument by Klepsch et al. (2017), which covers all three aspects of cognitive load.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Klepsch et al. (2017) source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Each group of up to seven participants was randomly assigned to one of the two conditions.

    “Each group of up to seven participants was randomly assigned to one of the two conditions.”
    Quote in the paperSubstantial claim
  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    Chatbot experience was assessed with three items with a Cronbach's alpha of 0.68.

    “Chatbot experience was assessed with three items on the frequency of chatbot use at home and school, the scale adapted from Thompson (2013), with a Cronbach's alpha of 0.68.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Thompson (2013) source

      Not checked in the free run.

  • Classified as probably not a substantial claim. May combine two claims.

    Interpretationcitation

    As chatting with a chatbot can be perceived as familiar, overlearned, and lifelike, learners might not perceive the manifold indirect affordances of the chatbot, underutilize them, and invest too little effort.

    “As chatting with a chatbot can similarly be perceived as familiar, overlearned, and lifelike, a similar phenomenon might occur: Learners might not perceive the manifold indirect affordances of the chatbot, underutilize them, and invest too little effort, as suggested in a recent study by Stadler et al. (2024).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Stadler et al., 2024 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Cognitive load increases with the number of mental processes performed simultaneously.

    “Cognitive load increases with the number of mental processes performed simultaneously (Sweller, 2010).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Sweller, 2010 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationreasoning

    Learners might quickly adapt to the chatbot's affordance and enter the habit of learning from texts.

    “The learners might quickly adapt to this affordance and enter the habit of learning from texts.”
    Quote in the paperNot a substantial claim
  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Interpretationreasoning

    Using generative AI as a tool for complex tasks without shortcuts might add a further layer of complexity and thereby cognitive load.

    “However, using generative AI as a tool for complex tasks without shortcuts might add a further layer of complexity and thereby cognitive load.”
    Quote in the paperNot a substantial claim
  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Interpretationreasoning

    In this study, the adapted chatbot responses might have led to more readability but also to less challenging content which led to shallower learning.

    “Similarly, in this study, the adapted chatbot responses might have led to more readability but also to less challenging content which led to shallower learning.”
    Quote in the paperNot a substantial claim
  • May combine two claims.

    Interpretationcitation

    This perception of the chatbot as 'easy' suggests an underinvestment of mental effort and, combined with students' moderate prior experience, a potential overestimation of their ability to effectively use these tools for learning.

    “This perception of the chatbot as”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites Salomon, 1984 source

      Not checked in the free run.

    • cites Stadler et al., 2024 source

      Not checked in the free run.

  • May combine two claims.

    Interpretationreasoning

    Since no standard for effective learning with chatbots was provided in this study, students may have set a low bar, a common pattern in self-regulated learning.

    “Since no standard for effective learning with chatbots was provided in this study, students may have set a low bar, a common pattern in selfregulated learning.”
    Quote in the paperSubstantial claim
  • May combine two claims. The quote only partly states this claim.

    Interpretationown data

    Using the full range of chatbot capabilities in self-regulated learning might still be 'tough', but this can be effectively alleviated by targeted support.

    “Using the full range of chatbot capabilities in self-regulated learning might still be”
    Quote in the paperSubstantial claim
  • May combine two claims.

    Interpretationreasoning

    While the findings show immediate benefits in terms of increased use of adaptation prompts, one cannot draw conclusions about how this might impact learning outcomes or self-regulated learning skills over extended periods of use and in other contexts.

    “While the findings show immediate benefits in terms of increased use of adaptation prompts, one cannot draw conclusions about how this might impact learning outcomes or self-regulated learning skills over extended periods of use and in other contexts.”
    Quote in the paperSubstantial claim
  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).

    Interpretationnone given

    In everyday use, students would likely combine the chatbot with web search and other tools, possibly to differing degrees.

    “In everyday use, students would likely combine the chatbot with web search and other tools, possibly to differing degrees.”
    Quote in the paperNot a substantial claim
  • May combine two claims.

    Interpretationown data

    As there is no significant difference between the groups in intrinsic or germane cognitive load, the demand characteristics effect, if present, is not very pronounced.

    “However, as there is no significant difference between the groups in intrinsic or germane cognitive load, this effect, if present, is not very pronounced, i.e., the experimental group did not perceive the task with adaptation guidance as substantially more complex and did not invest substantially more effort.”
    Quote in the paperNot a substantial claim
  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).

    Interpretationnone given

    Possibly, there is an aspect of self-disclosure when students opt for shorter answers in simple language.

    “Possibly, there is an aspect of self-disclosure when students opt for shorter answers in simple language.”
    Quote in the paperNot a substantial claim
  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Interpretationreasoning

    The intervention in this study does not require significant resources, and therefore even small effects would be of interest so that a larger sample would have been desirable.

    “The intervention in this study, however, does not require significant resources and, therefore, even small effects would be of interest so that a larger sample would have been desirable.”
    Quote in the paperNot a substantial claim
  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductnone given

    The experimental group was not just given hints on how to use adaptation prompts but also that it is beneficial to use them.

    “The experimental group was not just given hints on how to use adaptation prompts but also that it is beneficial to use them.”
    Quote in the paperNot a substantial claim
  • May combine two claims.

    Interpretationreasoning

    The feature to change language level and length was perceived as useful and could be more relevant for learners with lower language skills.

    “Still, the feature was perceived as useful and could be more relevant for learners with lower language skills.”
    Quote in the paperNot a substantial claim
  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based). May combine two claims.

    Interpretationnone given

    Alternatively, students might have felt they missed out on important information if they had simplified all the chatbot's answers and therefore preferred targeted adaptations to individual messages.

    “Alternatively, students might have felt they missed out on important information if they had simplified all the chatbot's answers and therefore preferred targeted adaptations to individual messages.”
    Quote in the paperNot a substantial claim
60 of 60
  • The paper relies on this without support.

    Using more adaptation prompts improves students' self-regulated learning.

    “potentially improving their self-regulated learning experiences”
  • The paper relies on this without support.

    The adaptation guidance intervention is easily implementable in real educational settings.

    “easily implementable interventions”
  • The paper relies on this without support.

    The interaction patterns of 9th-10th graders in a 20-minute session generalize to K-12 students.

    “This study aims to address this knowledge gap by investigating K-12 learners' perceptions and interaction patterns with genAI chatbots”
  • The paper relies on this without support.

    The LASSI-HS 'Processing Information' subscale is a valid measure of SRL skills in this sample despite low reliability (α = 0.60).

    “in this study, the subscale reached only a Cronbach's alpha of 0.60.”
  • The paper relies on this without support.

    The coding of off-topic conversation is reliable.

    “There is more off-topic conversation in the control group than in the group with adaptation guidance”
  • The paper relies on this without support.

    Chatbots like ChatGPT are fine-tuned to be assistants rather than conversationalists, which often results in verbose, encyclopedic answers.

    “The fact that chatbots like ChatGPT are fine-tuned to be assistants rather than conversationalists often results in verbose, encyclopedic answers.”
6 of 6

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?

  • The feedback literacy and self-regulated learning objective aims to strengthen students' capacity to understand, act on, and self-regulate in response to AI-generated feedback.

    “This objective aims to (1) strengthen students' capacity to understand, act on, and selfregulate in response to AI-generated feedback [124-127];”

    From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [127]

    The 'Supporting learning with chatbots' section recommends instruction and design changes to help students use chatbots for self-regulated learning. The paper mentions that chatbots can generate feedback, but it does not address students’ capacity to understand and act on AI-generated feedback or a feedback-literacy objective. The available passages have no page numbers. (LLM, conf=0.78)

    Experimental — accuracy not yet measured
  • GenAI serves as a cognitive scaffold by collecting student input in real time, adaptively modifying examples and prompts, and integrating support functions such as simplified language, summarization, and length control within the same workspace.

    “First, GenAI serves as a cognitive scaffold. By leveraging conversational interfaces, the system collects student input in real time, adaptively modifies examples and prompts, and integrates support functions such as simplified language, summarization, and length control within the same workspace.”

    From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [127]

    Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

    Experimental — accuracy not yet measured
  • When AI use lacks clear scaffolding, when students' tool-use competence is overestimated, or when tasks drift away from the complex, dynamic demands of authentic communities, GenAI can become an obstacle rather than an aid to practice.

    “When AI use lacks clear scaffolding, when students' tool-use competence is overestimated [127], or when tasks drift away from the complex, dynamic demands of authentic communities, GenAI can become an obstacle rather than an aid to practice.”
  • These gains tend to depend on structured pedagogical design such as adaptive questioning, error analysis, or project-based learning.

    “Notably, these gains tend to depend on structured pedagogical design such as adaptive questioning [127,128], error analysis [77,103], or project-based learning [108].”

    From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [127]

    Citation [108] is attached to the project-based-learning example. The Research setup describes a 20-minute exploratory task on cognitive biases, not project-based learning, and the Knowledge gains section reports no significant difference between the study conditions. A search for project-based learning found no passage in our copy addressing whether gains depend on it. (LLM, conf=0.74)

    Experimental — accuracy not yet measured

Statistics recomputed

Every reported test result, recomputed from its test statistic and degrees of freedom. A result shows as not adding up only once an independent check has confirmed it.

  • ConsistentF(3, 102) = 13.978reported p < .001 · recomputed p < .001

    “F(3, 102) = 13.978,p < .001”

  • ConsistentF(1, 104) = 41.085reported p < .001 · recomputed p < .001

    “F(1, 104) = 41.085,p < .001”

  • ConsistentF(1, 104) = 0.886reported p = .349 · recomputed p = .349

    “F(1, 104) = 0.886, p = .349”

  • ConsistentF(1, 104) = 0.202reported p = .654 · recomputed p = .654

    “F(1, 104) = 0.202, p = .654”

4 of 4

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

  • Button-use percentage does not match the participant count

    Minor

    The experimental group had 53 participants, so 17 participants represent 32.1%, not 27%.

    Reported 27 · recomputed 32.075472

1 of 1

Cites

Flagged first, then by citations

Research works printed but not linked: 2

  1. Abbasi, S., Kazi, H., & Hussaini, N. (2019). Effect of chatbot systems on student’s learning outcomes. Sylwan, 163(10), 49–63.
  2. Hayes, A. F. (2017). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach (Second edition.). The Guilford Press.

Cited by

Sorted by citations

Authors
Klar, M.
Affiliations
University of Duisburg-Essen (DE)
Corresponding author
Klar, Maria
Venue
Smart Learning Environments
Published
2025-05-08
Volume
12
Issue
1
ISSN
2196-7091 (ISSN-L)
OpenAlex
W4410187407
Cited by
39
References
45
Citations by year
2026: 33 · 2025: 6
FWCI
15.77
Type
journal article
Language
en
Open access
Locations
  • Smart Learning Environments (publishedVersion, cc-by)
  • Universitätsbibliographie, Universität Duisburg-Essen (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • DuEPublico (University of Duisburg-Essen) (submittedVersion, cc-by)
Funders
Universität Duisburg-Essen
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
Keywords
generative AI chatbots, K-12 students, student self-regulation, content adaptation, instructional prompts, cognitive load, learner perceptions, adaptation guidance, high school students, knowledge improvement, student satisfaction

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.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-06.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-06.

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