R-I-Z-A-based assessment found satisfactory qualitative outcomes: 86% improvement in resources, 81% excellent interpretation performance, and 76% able to produce a medial message¶
Claim · All claims
Evidence · 1 study (3 entries) · causalr1·q2
Currency · newest study 2016 · checked against its sources 2026-11-02 (automated, 3 of 3 entries) · not reviewed by a person
Subclaims¶
Reading the evidence codes
q is the design tier, i the impact, n the sample, and the kind with its r
the rigour judged within that kind: what each code means.
This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q2 i? Comparing beginning and end of the trial, the resources component showed a significant improvement (86%), especially in identifying key concepts, their definition and linking. → Feola 2016
q2 i? 81% of participants achieved excellent performance levels in analysing a media text, giving value judgments on the medial relationship, recognising private emotions and narrating the experience. → Feola 2016 (2)
q2 i? By the end, 76% of learners could produce a medial message using media linguistic rules, 72% could discriminate facts and actions from personal opinions, and 80% could select relevant information discarding the superfluous. → Feola 2016 (3)
Evidence¶
Feola 2016¶
Elvia Ilaria Feola. (2016). Digital Literacy and New Technological Perspectives. Universal Journal of Educational Research 4(9): 2174-2180. https://doi.org/10.13189/ujer.2016.040929
q2 · i? · causal · r1
Qualitative R-I-Z-A assessment of the same 162-student one-group e-learning course, comparing competence profiles at the beginning and end of the trial. The article reports "a significant improvement (86%)" in the resources component, keyed to identifying, defining and linking key concepts. The percentage is descriptive.
"taking into consideration the evaluation of resources, implementing a comparison on the digital skills of learners at the beginning of the trial and the end, you can highlight a significant improvement (86%), especially as regards the identification of the key concepts, their definition and the linking."
Feola 2016 (2)¶
Elvia Ilaria Feola. (2016). Digital Literacy and New Technological Perspectives. Universal Journal of Educational Research 4(9): 2174-2180. https://doi.org/10.13189/ujer.2016.040929
q2 · i? · causal · r1
Interpretation-structures component of the R-I-Z-A evaluation, based on the difference of perceptions students expressed at the beginning and end of the experiment. The article reports that "81% of participants achieved excellent performance levels" across media-text analysis, value judgments, emotion recognition and narration.
"It was found that 81% of participants achieved excellent performance levels in analyzing a media text, to provide value judgments on the medial relationship, recognizing the private emotions and in narrating the experience."
Feola 2016 (3)¶
Elvia Ilaria Feola. (2016). Digital Literacy and New Technological Perspectives. Universal Journal of Educational Research 4(9): 2174-2180. https://doi.org/10.13189/ujer.2016.040929
q2 · i? · causal · r1
Action-structures component of the R-I-Z-A evaluation, derived from differences in learners' ability to design a media product or apply a storytelling model. The article additionally reports that 72% could discriminate facts and actions from personal opinions and 80% could select relevant information, discarding the superfluous.
"The 76% of the learners, at the end of the experiment is capable of producing a medial message using the media linguistic rules and evaluate a message."
Discussion¶
Learner Variables¶
- Academic and Critical Literacy — outcome: instruction changes it
- Oral Language — outcome: instruction changes it
Related Claims¶
- Expert validators rated the Corel VideoStudio Pro X7-based media very valid (97.7% material expert, 76.5% media expert) and a limited trial group rated it 93.06% — related
- Post-learning media products spanned multiple mathematics topics: 42.8% geometry-related props, 28.57% arithmetic-related props, 51.43% could explain prop creation, and 60% could use shapes to run their code — related
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