The exploration of continuous learning intention in STEAM education through attitude, motivation, and cognitive load

Wu, Liu, Huang · International Journal of STEM Education · 2022 · education · 10.1186/s40594-022-00346-y · record Wu2022-the-exploration-of-continuous-learning-inten
tag layer · index · concepts · authors · עברית
Where this record's text came from. faceted 2026-08 by reading the locally held text (pdftext); every evidence string verified as an exact substring of that text before merging. method is coded 'behavioural-experiment' as the nearest allowed value: this is a post-activity questionnaire survey analysed with PLS-SEM (self-described as an 'empirical experiment'), not an intervention with a control group. Claim type 'mechanism' reflects the mediated-moderation model — the claim is about why/through what path intention arises. The source is pdftext with soft-hyphen line-break artifacts inside many sentences; quotes were deliberately chosen from artifact-free sentences so the verbatim check cannot be broken by hyphenation. A further 'in line with' relation to Findik-Coşkunçay et al. (2018) was left out because its sentence carries an extracted minus-sign glyph. 2026-08-14, 2026-08-25 and 2026-08-26 schema-0.3 passes: every quote verified as an exact substring of the staged text and anchored at merge time; concept terms verified present; every edge endpoint an existing node.
How to read this page. The article itself is not reproduced here — this paper is not cleared for redistribution, so what follows is the tag layer alone. The evidence sentences are withheld with the article. The table at the foot lists every tag the record carries; each row names the facet it belongs to, and the whose words column says whether the tag records the paper's own wording or the tagger's sentence about the paper. Every tag links to each other paper in the corpus carrying it. The machine-readable edition of the same thing is the TEI file beside this one, where the tags live in standOff, and the article is at its publisher via the link below. When we have changed our mind. Some entries in the table begin with a word in capitals and the reason for it. EVIDENCE CORRECTED — the finding still stands, but we had quoted the wrong sentence from the paper, and the quotation has been replaced with the right one. RETRACTED — the entry itself was wrong; it stays on the page, marked, with the reason, rather than being deleted. WITHDRAWN AND REPLACED — the entry was wrong, and a corrected version of it appears in the entries below. Each mark carries its own reason, in brackets, because the reasons differ from one entry to the next. An entry we have WITHDRAWN is removed from this page and kept in the record, with its reason. A line reading Audit and a date is a later re-reading of the entry against its whole sentence: DOUBTFUL means it was kept, and the reason says what is loose about it. Quotation marks inside the tagger's sentence. Where a tag is the tagger's own sentence, a phrase in quotation marks inside it is borrowed from the paper — the tagger's wording around it is not. The paper's own sentence is the evidence quote for that row; on this page it is withheld with the article, and the article is at its publisher. Nothing inside quotation marks anywhere on this page is ours: if it is quoted, it is the paper's. Whose words a concept carries. A concept entry records a term the paper itself uses, so the term, the sense given for it, and its evidence are the paper's own words, quoted where the paper fixes them. This is the opposite of a sense entry in the tag table, which is the tagger's sentence about how the paper uses a term. Where a concept entry could not be grounded in the paper's words, the entry says so on its own row.
Other fields define these differently the same word, defined another way in another discipline
cognitive load 3 fields · bootstrap 2 fields · discriminant validity 2 fields

Tags on this paper

Every tag the record carries, each linking to every other paper in the corpus that carries it. A tag appears here whether or not its words occur in the article — the spans below are only the ones a sentence in this paper licenses. Of the 5 concept tags on this paper, all 5 are grounded in a quoted sentence. 2 carry the tagger's gloss of what the term means in this paper, which is not something the article can license.
cognitive load mental effort discriminant validity mental load ARCS successfully carrying out the hands-on STEAM activity in the psychomotor phase raises the learner's attitude and motivation, which in turn produces the intention to keep learning a heavy cognitive load depresses learning performance because a learner cannot process the complexity and volume of the incoming information all at once high demand from cognitive processes such as recall, comprehension, application and analysis consumes capacity and thereby lowers the learner's perception of the material's usability continuous learning intention perceived usability STEAM learning cycle ARCS model learning attitude ARCS motivation structural equation modelling (partial least squares) partial least squares (PLS) confirmatory factor analysis confirmatory factor analysis (CFA) Cronbach's alpha Cronbach’s alpha coefficients composite reliability and average variance extracted CR values ... AVE values bootstrap variance inflation factor (multicollinearity check) coefficient of determination effect size multi-group comparison test partial least squares multi-group analysis (PLS-MGA) goodness-of-fit residual index SRMR value behavioural-experiment

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relation to other workclaim_relationshow this paper stands to another: agrees, contradicts, extends, qualifies
claim typeclaim_typethe shape of the claim: existence, mechanism, method, critique, prediction, null
concept edgeconcept_edgesan asserted relation between two concepts, with the sentence asserting it
conceptconceptsan idea the paper works with, quoted where the paper uses it
content tagcontent_tagsa finding, definition, quantity, statistic or variable named in the paper
controlcontrolsan experiment run to eliminate a rival explanation
limitationlimitationswhat the paper says its evidence cannot support
mechanismmechanismshow the reported effect is said to come about
methodmethodhow the paper produced its evidence
phenomenonphenomenonthe effect or regularity under study
sensesensesa distinct use of a term, quoted where the paper fixes it
transfertransfersa method or concept carried in from another field

The paper

The full text is not reproduced here. This article is not cleared for redistribution, so the page carries the tag layer only. Its evidence sentences are withheld; the grounding status remains with each tag, and the article itself is at https://doi.org/10.1186/s40594-022-00346-y. The reading view exists for the papers whose licence permits it.

Every tag on this page

claim_relations 2 · claim_type 1 · concept_edges 2 · concepts 5 · content_tags 38 · controls 2 · limitations 6 · mechanisms 3 · method 1 · phenomenon 1 · senses 4 · transfers 1

Relations on this page carry a quotation for the claim. Where a relation was separately evidenced — and so tested against the vocabulary for its type — the row says so; 1 of 2 relations here carries that mark. The rest are the tagger’s reading of the sentence quoted beside them.

facettagfieldconf.whose words
claim_typemechanism
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claim_typethe paper's words
phenomenoncontinuous learning intention in STEAM education
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phenomenonthe paper's words
methodbehavioural-experiment
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methodthe paper's words
mechanismsmechanisms
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mechanisms[0]the tagger's words
mechanismsmechanisms
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mechanisms[1]the tagger's words
mechanismsmechanisms
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mechanisms[2]the tagger's words
limitationsThe paper flags its own limitations explicitly before listing them.
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what this limits: the paper's own framing: DESPITE THE CONTRIBUTIONS OF THIS STUDY, SEVERAL LIMITATIONS REMAIN TO BE ADDRESSED
limitations[0]the tagger's words
limitationsThe sample comes from a single region of Taiwan.
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what this limits: the population the result speaks for: A SAMPLE OF STUDENTS FROM ONLY ONE REGION OF TAIWAN
limitations[1]the tagger's words
limitationsVariables linking AI-based STEM education to employability were not modelled.
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what this limits: any employability claim: THE LONG-STANDING UNSOLVED PROBLEM OF AI-BASED EDUCATION IN STEM STUDIES AND EMPLOYABILITY NEEDS TO BE CONSIDERED WITH OTHER POSSIBLE VARIABLES
limitations[2]the tagger's words
limitationsGeneralisation across two very different populations is established by the ABSENCE of a significant difference, which is an acceptance of the null.
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what this limits: the claim that this model holds for both elementary and university students: it rests on finding no significant difference between the two groups, not on a test of equivalence
limitations[3]1.0the tagger's words
limitationsItems were removed from the model until the validity thresholds were satisfied, so the thresholds were met partly by deletion.
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what this limits: the reported validity statistics: items were extracted from the model, after which all values exceeded the minimum threshold
limitations[4]1.0the tagger's words
limitationsParticipation was voluntary and recruitment happened in class after the activity, so the sample is self-selected among those who had just taken part.
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what this limits: this sample as representative of STEAM learners: students were recruited in the classroom after their learning activities and participated voluntarily
limitations[5]1.0the tagger's words
transferscognitive load theory, originally developed from short-term memory experiments, is imported as the cognitive-domain measure in a STEAM education acceptance model
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transfers[0]the tagger's words
controlsthe same learning topic used in both STEAM activities, with the materials made harder for the university group and easier for the elementary group
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eliminates: a difference between the two populations that is really a difference in whether they could follow the material at all - the topic is held constant and the difficulty is matched to each · outcome (stated by the tagger, no quotation): held
controls[0]0.85the tagger's words
controlsthe same questionnaire administered after both activities, in the university and in the elementary school
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eliminates: an instrument effect - two different questionnaires would make the two settings incomparable whatever the activities did · outcome (stated by the tagger, no quotation): held
controls[1]0.85the tagger's words
conceptscognitive load
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concepts[0]the paper's words
conceptsmental effort
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also in: mental effort
concepts[1]the paper's words
conceptsdiscriminant validity
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concepts[2]the paper's words
conceptsmental load
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also in: mental load
concepts[3]0.95the paper's words
conceptsARCS
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also in: ARCS
concepts[4]0.9the paper's words
sensescognitive load - operationalised here as TWO components, mental load and mental effort, inside a model that also carries technology-acceptance and motivation constructs
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senses[0]1.0the tagger's words
sensesgeneralization - established by a NON-SIGNIFICANT group difference rather than by sampling both populations to a defined standard
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senses[1]1.0the tagger's words
senses`cognitive load` - A TWO-PART PARTITION WHOSE HALVES ARE EASILY CONFLATED, AND THIS PAPER KEEPS THEM APART. `Quotation withheld` The names differ by one word and both read as `how hard it feels`. The distinction is between what the TASK imposes and what the LEARNER expends, and a corpus that carries only one of the two - as this record did - silently makes `cognitive load` mean whichever half it kept.
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senses[2]0.95the tagger's words
senses`ARCS` - AN ACRONYM WHOSE LETTERS ARE ITS PARTITION, LIKE `WEIRD` IN `henrich2010`. `Quotation withheld.` The name cannot drift from its content because the content spells the name - and the same sentence then gives `satisfaction` a SECOND abbreviation, `SAT`, so one construct carries two acronyms at different levels.
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senses[3]0.85the tagger's words
claim_relationsextends → Weng et al. (2018)
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claim_relations[0]the tagger's words
claim_relationsreplicates → Davis, 1989; Davis et al., 1989 (TAM)
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claim_relations[1]the tagger's words
concept_edgesmental effort —part-of→ cognitive load
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strength of the relation: 1
concept_edges[0]the tagger's words
concept_edgesmental load —part-of→ cognitive load
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the relation itself is separately evidenced · strength of the relation: 1 · note: 'consists of' is the containment cue, and it is in the gate's list - so unlike most of tonight's edges this one is actually cue-tested. Direction: the whole is named first here, the parts second, which is the 'CONTAINER_FIRST' order.
concept_edges[1]0.95the tagger's words
content_tagsstructural equation modelling (partial least squares)
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content_tags.statistics[0]the tagger's words
content_tagsconfirmatory factor analysis
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content_tags.statistics[1]the tagger's words
content_tagsCronbach's alpha
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content_tags.statistics[2]the tagger's words
content_tagscomposite reliability and average variance extracted
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content_tags.statistics[3]the tagger's words
content_tagsbootstrap
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also in: bootstrap
content_tags.statistics[4]the tagger's words
content_tagsvariance inflation factor (multicollinearity check)
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content_tags.statistics[5]the tagger's words
content_tagscoefficient of determination
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content_tags.statistics[6]the tagger's words
content_tagseffect size
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also in: effect size
content_tags.statistics[7]the tagger's words
content_tagsmulti-group comparison test
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content_tags.statistics[8]the tagger's words
content_tagsgoodness-of-fit residual index
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content_tags.statistics[9]the tagger's words
content_tagsPerceived usability had a direct positive effect on continuous learning intention and also strengthened the link between learning attitude and intention.
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content_tags.findings[0]the tagger's words
content_tagsCognitive load had a significant negative direct effect on perceived usability (B = -0.32), so lower load meant higher perceived usability.
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content_tags.findings[1]the tagger's words
content_tagsARCS motivation had a positive and significant effect on learning attitude (B = 0.48).
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content_tags.findings[2]the tagger's words
content_tagsBoth moderation terms were significant: perceived usability moderated attitude to intention (B = 0.104) and ARCS moderated perceived usability to attitude (B = 0.082).
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content_tags.findings[3]the tagger's words
content_tagsThe attitude-to-intention relationship was steeper for learners with high perceived usability than for those with low perceived usability.
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content_tags.findings[4]the tagger's words
content_tagsThe core TAM paths were supported: perceived usability to attitude (B = 0.41) and attitude to intention (B = 0.34).
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content_tags.findings[5]the tagger's words
content_tagsNone of the model's paths differed significantly between the elementary-school and university subsamples, so the model held for both age groups.
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content_tags.findings[6]the tagger's words
content_tagsThe structural model fitted the data well, with SRMR of 0.069 and RMS_theta of 0.16.
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content_tags.findings[7]the tagger's words
content_tagscontinuous learning intention
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content_tags.definitions[0]the tagger's words
content_tagsperceived usability
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content_tags.definitions[1]the tagger's words
content_tagscognitive load
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content_tags.definitions[2]the tagger's words
content_tagsSTEAM learning cycle
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content_tags.definitions[4]the tagger's words
content_tagsARCS model
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also in: ARCS model
content_tags.definitions[5]the tagger's words
content_tagsMental load
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also in: Mental load
content_tags.definitions[6]the tagger's words
content_tagsmental effort
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also in: mental effort
content_tags.definitions[7]the tagger's words
content_tagscognitive load
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content_tags.variables[0]the tagger's words
content_tagscontinuous learning intention
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content_tags.variables[1]the tagger's words
content_tagslearning attitude
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content_tags.variables[2]the tagger's words
content_tagsARCS motivation
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content_tags.variables[3]the tagger's words
content_tagsperceived usability
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content_tags.variables[4]the tagger's words
content_tags145 — questionnaire responses collected, of which 141 were valid
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content_tags.quantities[0]the tagger's words
content_tags84 undergraduate students and 57 elementary students — composition of the voluntary survey sample
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content_tags.quantities[1]the tagger's words
content_tags7-point Likert scale — response format of the 52-item instrument (24 TAM, 8 cognitive load, 20 ARCS items)
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content_tags.quantities[2]the tagger's words
content_tagsB = − 0.32, p < 0.01 — path coefficient from cognitive load to perceived usability
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content_tags.quantities[3]the tagger's words
content_tagsB = 0.48, p < 0.01 — path coefficient from ARCS motivation to learning attitude
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content_tags.quantities[4]the tagger's words
content_tagsB = 0.104, t-value = 3.13, p = 0.002 — interaction (moderation) effect of perceived usability on the attitude-intention path
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content_tags.quantities[5]the tagger's words
content_tags0.069 — SRMR value for the saturated model, indicating acceptable fit
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content_tags.quantities[6]the tagger's words
content_tags0.96 — Cronbach's alpha for the perceived usability construct
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content_tags.quantities[7]the tagger's words

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