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 accessAbstract
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.
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Cites
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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
- Findingnone given
In this study, in neither of the three types of load there was a significant difference.
“In this study, in neither of the three types of load there was a significant difference.”
Quote in the paperSubstantial claim - Findingown data
There are no significant differences between the conditions when breadth, depth, and precision aspects of knowledge tests are tested separately.
“However, there are no significant differences between the conditions when these aspects are tested separately.”
Quote in the paperSubstantial claim - Findingown data
Participants in the experimental condition used twice as many adaptation prompts.
“The participants in the experimental condition, i.e., with adaptation guidance, used twice as many adaptation prompts.”
Quote in the paperSubstantial claim - Findingown data
27% of the participants in the experimental group used one of the length/language options at least once.
“These options were used only by a minority: 27% (17) of the participants in the EG used one of the options at least once.”
Quote in the paperNot a substantial claim - Findingown data
For none of the hypothesized moderations a significant interaction was found for extraneous load and knowledge gain.
“For none of these hypothesized moderations a significant interaction was found.”
Quote in the paperSubstantial claim - Findingown data
Learners do not perceive the chatbot as providing answers more adapted to their needs in the group with adaptation guidance than in the group without.
“Learners do not perceive the chatbot as providing answers more adapted to their needs in the group with adaptation guidance than in the group without.”
Quote in the paperSubstantial claim - Findingown data
Learners in both groups reported high overall satisfaction.
“reported high satisfaction levels”
Quote in the paperNot a substantial claim - Findingown data
Participants in the experimental group used a larger variety of adaptation prompts.
“They also used a larger variety of adaptation prompts.”
Quote in the paperNot a substantial claim - Findingown data
The experimental group used significantly more adaptation prompts.
“They also used significantly more adaptation prompts.”
- Also stated in: § Adaptation prompts · plain
“In terms of the main effects hypothesized in this study, only the difference in number of adaptation prompts was significant.”
Quote in the paperSubstantial claim - Also stated in: § Adaptation prompts · plain
- Findingown data
A third of the participants without adaptation guidance did not use any adaptation prompt, not even 'Give an example.'
“Overall, a third of the participants without adaptation guidance did not use any adaptation prompt, not even”
Quote in the paperSubstantial claim - Findingown data
Only 27% of the students in the experimental group changed the language level or response length at least once by using the respective buttons.
“In contrast, only 27% of the students in the EG changed the language level or response length at least once by using the respective buttons.”
Quote in the paperSubstantial claim - Findingown data
The experimental group posed significantly more questions (M = 7.8) than the control group (M = 4.8).
“Taking all forms of questions together, the EG posed significantly more questions (p <.001; M = 7.8) than the control (M = 4.8).”
Quote in the paperSubstantial claim - Findingown data
On average, students were readily satisfied with their chatbot interaction.
“On average, students judged their competence as high despite moderate prior experience, and they were readily satisfied with their chatbot interaction.”
Quote in the paperNot a substantial claim - Findingown data
83% of the participants in the experimental group used at least one of the next prompts suggested by the chatbot.
“For example, 83% of the participants in the EG used at least one of the next prompts suggested by the chatbot.”
Quote in the paperNot a substantial claim - Findingown data
The differences between pre- and post-test scores were neither significantly higher nor lower in the experimental group (M = 2.43) than in the control group (M = 2.52).
“The fact that the differences between pre-and post-test scores were neither significantly higher nor lower in the experimental group (M = 2.43) than in the control group (M = 2.52) is interesting because the chatbot interactions did show significant differences in terms of adaptation prompts, and also, descriptively in overall engagement operationalized by the number of questions posed overall and”
Quote in the paperSubstantial claim - Findingown data
The experimental group used about twice as many adaptation prompts (M = 6.0) as the control group (M = 2.5).
“The experimental group used twice as many adaptation prompts (M = 6.0) compared to the control group (M = 2.5)”
- Also stated in: § RQ3 and RQ4: hypothesis tests · plain
“The average number of adaptation prompts per session is 6 in the experimental group (written by learner and suggested by chatbot combined) and 2.51 in the control group.”
Quote in the paperSubstantial claim - Also stated in: § RQ3 and RQ4: hypothesis tests · plain
- Findingown data
The mean values do not differ significantly between the two groups for the items on learner satisfaction.
“The mean values do not differ significantly between the two groups for the items on learner satisfaction.”
Quote in the paperSubstantial claim - Findingreasoning
Extraneous load did not differ significantly between the groups.
“The fact that extraneous load did not differ significantly between the groups is in line with research by Abbasi et al. (2019) and contributes empirical evidence to the emerging research that looks into cognitive load while learning with chatbots.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Abbasi et al. (2019)
Not checked in the free run.
- Findingown data
The experimental group rated the supportive features favorably with an average agreement of 5.40.
“The experimental group rated the supportive features favorably with an average agreement of 5.40.”
Quote in the paperNot a substantial claim - Findingown data
The experimental group used almost twice as many adaptation prompts as the control group, not including suggested prompts.
“The students in the experimental group also used almost twice as many adaptation prompts, not including those adaptation prompts that were suggested by the chatbot in the EG.”
Quote in the paperSubstantial claim - Findingown data
The underutilization of core affordances, such as adapting answers to the learner's needs, becomes apparent in the fact that a third of the students without adaptation guidance did not query the chatbot for any adaptation.
“The underutilization of core affordances, such as adapting answers to the learner's needs becomes apparent in the fact that a third of the students without adaptation guidance did not query the chatbot for any adaptation.”
Quote in the paperSubstantial claim - Findingown data
Students with lower prior knowledge did not benefit more strongly from the adaptation guidance.
“Students with lower prior knowledge did not benefit more strongly from the adaptation guidance.”
Quote in the paperSubstantial claim - Findingown data
The feature to change the language level and length for all subsequent outputs was not used as often.
“In contrast, the feature to change the language level and length for all subsequent outputs was not used as often.”
Quote in the paperNot a substantial claim - Interpretationreasoning
The effect of trial-and-error resulting in high extraneous load, as predicted by cognitive load theory, does not occur because the range of options is not perceived by the learners.
“The effect of trialand-error resulting in high ECL, as predicted by cognitive load theory (Sweller, 2020), does not occur because the range of options is not perceived by the learners.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Sweller, 2020 source
Not checked in the free run.
- Interpretationown data
Hypothesis 3.3 (adaptation guidance leads to a larger knowledge gain) is not supported.
“Hypothesis 3.3, assuming a larger knowledge gain, is also not supported.”
Quote in the paperSubstantial claim - Interpretationown data
The ability to adapt individual messages by asking the chatbot to make them easier or explain step-by-step might have been more helpful for students than changing the length or language level for all following responses.
“Therefore, the ability to adapt individual messages by asking the chatbot to make them”
Quote in the paperSubstantial claim - Premisecitation
There is a gap in understanding how K-12 students interact with tools, particularly in adapting chatbot responses to individual needs.
“There is a gap in understanding how K-12 students interact with tools, particularly in adapting chatbot responses to individual needs.”
Quote in the paperSubstantial claim0 of 3 sources checked - Study design and conductown data
Conditions for moderation analysis were not met for the dependent variable adaptation prompts.
“Conditions for this method were not met for the dependent variable adaptation prompts.”
Quote in the paperSubstantial claim - Study design and conductown data
There were no significant differences between the two groups on moderator and control variables.
“There were no significant differences between the two groups on these variables.”
Quote in the paperSubstantial claim - Interpretationown data
The descriptively higher level of intrinsic cognitive load in the experimental group indicates that learners judged the task as slightly more complex than in the control group.
“The descriptively higher level of ICL in the EG indicates that learners judged the task as slightly more complex than in the control group.”
Quote in the paperNot a substantial claim - Interpretationreasoning
Through the instruction and the supportive features, functioning as reminders, the experimental group likely perceived added task demands in terms of metacognition and self-regulation.
“Through the instruction and the supportive features, functioning as reminders, i.e., as instructional prompts, the experimental group likely perceived added task demands in terms of metacognition and self-regulation.”
Quote in the paperNot a substantial claim - Interpretationreasoning
Extraneous load might not be elevated because chatting with a chatbot is intuitive at the surface level.
“Extraneous load (ECL) might not be elevated because chatting with a chatbot is intuitive at the surface level.”
Quote in the paperSubstantial claim - Interpretationown data
Hypothesis 3.2 (adaptation guidance leads to reduced extraneous load) is not supported.
“Hypothesis 3.2, assuming a reduced extraneous load, is not supported.”
Quote in the paperSubstantial claim - Interpretationreasoning
The reasons for the encyclopedic outputs lie both within the chatbot and the users.
“The reasons for this lie both within the chatbot and the users.”
Quote in the paperSubstantial claim- Rests on an assumption: Chatbots like ChatGPT are fine-tuned to be assistants rather than conversationalists, which often results in verbose, encyclopedic answers.
- Interpretationown data
Hypothesis 3.1 (adaptation guidance leads to a higher number of adaptive prompts) is supported by the data.
“Therefore, hypothesis 3.1, stating that adaptation guidance leads to a higher number of adaptive prompts is supported by the data.”
Quote in the paperSubstantial claim - Interpretationown data
Even a short introduction on adaptation prompts like 'Give me a summary' or 'Make it easier', in combination with easily implementable additions to the chatbot interface, suffices to help students adapt the chatbot responses to their needs more often.
“First, even a short introduction on adaptation prompts like”
Quote in the paperSubstantial claim - Interpretationown data
Modest interventions can potentially enhance students' interaction with chatbots.
“This indicates that modest interventions can potentially enhance students' interaction with chatbots.”
Quote in the paperSubstantial claim - Interpretationreasoning
Students may have rated their skills positively because they lacked a concrete standard of effective chatbot interaction.
“The students may have rated their skills positively because they lacked a concrete standard of effective chatbot interaction.”
Quote in the paperSubstantial claim - Study design and conductreasoning
The short-term nature of this study (a single, 20-min interaction) may not fully capture the potential long-term effects of adaptation guidance.
“Fourth, it is important to note the short-term nature of this study.The research focused on a single, 20-min interaction with a chatbot, which may not fully capture the potential long-term effects of adaptation guidance.”
Quote in the paperNot a substantial claim - Interpretationcitation
If the control group does not perceive self-regulation to be necessary, then there is not a high level of extraneous load that needs reduction to begin with.
“If the control group does not perceive self-regulation to be necessary, then there is not a high level of extraneous load that needs reduction to begin with (Seufert, 2018).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Seufert, 2018 source
Not checked in the free run.
- Interpretationown data
The lack of significant difference between the conditions shows that adaptation guidance does not lead to significantly lower knowledge gains.
“The lack of significant difference between the conditions also shows that adaptation guidance does not lead to significantly lower knowledge gains.”
Quote in the paperSubstantial claim - Interpretationreasoning
Given that genAI chatbots are relatively new and students had low prior experience, it is likely they have not yet developed knowledge of effective chatbot interaction.
“Given that genAI chatbots are relatively new and students had low prior experience, it is likely they have not yet developed knowledge of effective chatbot interaction.”
Quote in the paperSubstantial claim - Interpretationown data
Even brief instruction on adaptation prompts can significantly influence how students interact with chatbots.
“Second, the results demonstrate that even brief instruction on adaptation prompts can significantly influence how students interact with chatbots.”
Quote in the paperSubstantial claim - Study design and conductreasoning
There is a limitation to the study's ecological validity: students did not have access to web search and were restricted to the chatbot.
“Second, while the premise of the study is close to an authentic setting, i.e., conducting research on an unfamiliar topic with the help of a chatbot, there is a limitation to its ecological validity: Students did not have access to web search and were restricted to the chatbot.”
Quote in the paperNot a substantial claim - Study design and conductreasoning
There might have been unintended demand characteristics to the instructional pointers on adaptation prompts that undermine an effect on extraneous load.
“First, there might have been unintended demand characteristics to the instructional pointers on adaptation prompts that undermine an effect on extraneous load.”
Quote in the paperNot a substantial claim - Study design and conductnone given
The sample size is not large enough to detect small effects.
“Third, the sample size is not large enough to detect small effects.”
Quote in the paperNot a substantial claim - Premisecitation
The self-regulated learning skills that are necessary to effectively use chatbots during research are also necessary to evaluate one's own performance.
“Dunning et al., (2003) dub this the”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Dunning et al., (2003) source
Not checked in the free run.
- 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.
FindingreasoningParticipants' 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 claimMay combine two claims.
Findingown dataParticipants 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 claimMay combine two claims. The quote only partly states this claim.
Findingown dataAdaptation 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- Also stated in: § RQ3 and RQ4: hypothesis tests · plain
May combine two claims.
Findingown dataThe 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 claimMay combine two claims.
Findingown dataMany 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 claimMay combine two claims.
Findingown dataOverall, 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 claimMay combine two claims.
Findingown dataThere 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 claimMay combine two claims.
FindingcitationComplex, 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 dataOn 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 claimMay combine two claims.
Findingown dataThe 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 claimMay combine two claims.
Findingown data18% 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 claimMay combine two claims.
Findingown dataIn 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 claimThe quote only partly states this claim.
Findingown dataKnowledge 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- Also stated in: § RQ3 and RQ4: hypothesis tests · plain
May combine two claims.
Findingown dataDescriptively, 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 claimMay combine two claims.
Findingown dataStudents 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 claimMay combine two claims.
Findingown dataThere 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 claimMay combine two claims.
Findingown dataIrrespective 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 claimMay combine two claims.
Findingown dataStudents 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 claimMay combine two claims.
Findingown dataThe 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 claimMay combine two claims.
Findingown dataStudents 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 claimMay combine two claims.
Findingown dataPrior 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 claimMay combine two claims.
Interpretationown dataHypotheses 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 claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationTasks 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).
InterpretationcitationStudents 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.
InterpretationcitationLearners 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 claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
InterpretationreasoningDeciding among adaptation options can induce cognitive load.
“Deciding among these adaptation options can induce cognitive load.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationown dataGiven 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 claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.
InterpretationreasoningChanging 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 claimMay combine two claims.
Interpretationown dataEven 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 claimMay combine two claims.
InterpretationcitationThe 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 given106 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 claimMay combine two claims.
Interpretationown dataEasily 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 dataThe 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 claimClassified as probably not a substantial claim.
Study design and conductown dataKnowledge 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- Also stated in: § Instruments · plain
May combine two claims.
Interpretationown dataExtensive '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 claimMay combine two claims.
InterpretationreasoningIn 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 claimProbably not a substantial claim: may not pass S3 (load-bearing).
InterpretationreasoningSelf-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 claimMay combine two claims.
InterpretationreasoningBecause 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 claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
InterpretationreasoningThere 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 claimMay combine two claims.
InterpretationreasoningThe 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 claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductreasoningThis 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 claimClassified as probably not a substantial claim.
Study design and conductcitationCognitive 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 givenEach 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 claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown dataChatbot 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.
InterpretationcitationAs 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).
PremisecitationCognitive 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).
InterpretationreasoningLearners 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 claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
InterpretationreasoningUsing 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 claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
InterpretationreasoningIn 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 claimMay combine two claims.
InterpretationcitationThis 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 checkedMay combine two claims.
InterpretationreasoningSince 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 claimMay combine two claims. The quote only partly states this claim.
Interpretationown dataUsing 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 claimMay combine two claims.
InterpretationreasoningWhile 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 claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Interpretationnone givenIn 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 claimMay combine two claims.
Interpretationown dataAs 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 claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Interpretationnone givenPossibly, 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 claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
InterpretationreasoningThe 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 claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductnone givenThe 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 claimMay combine two claims.
InterpretationreasoningThe 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 claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based). May combine two claims.
Interpretationnone givenAlternatively, 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
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.”
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 measuredGenAI 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 measuredWhen 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.”
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]
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”
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Button-use percentage does not match the participant count
MinorThe experimental group had 53 participants, so 17 participants represent 32.1%, not 27%.
Reported 27 · recomputed 32.075472
“27% (17) of the participants in the EG used one of the options at least once.”
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Thematic and Task-Based Categorization of K-12 GenAI Usages with Hierarchical Topic Modeling
Schneider, J., Hasler, B. S., Varrone, M., Hoya, F., Schroffenegger, T., Mah, D.-K., & Peböck, K. (2026) · Communications in computer and information science · doi:10.1007/978-3-032-16451-3_18 · Cited by 2 · see citing works
Meta-analysis on the influence of AI agents on K-12 student cognitive performance
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EFFICIENCY, ENGAGEMENT, AND COGNITIVE OFFLOADING: A REVIEW OF GENERATIVE AI IN EDUCATION
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Factors influencing accounting students attitudes towards AI tools in higher education using PLS SEM
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Perceptions, Uses, and Attitudes Towards ChatGPT Among University Students in the Field of Education
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Sequence Analysis for Understanding Constructionist Learning in AI Education
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PAKISTANI ESL UNDERGRADUATES' PERCEPTIONS ABOUT THE ROLE OF CHATGPT IN ACADEMIC WRITING
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- Authors
- Klar, M.
- Affiliations
- University of Duisburg-Essen (DE)
- Corresponding author
- Klar, Maria
- ORCID
- 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
- gold
- doi.org
- 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
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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.
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