Cited by 302Visual and Cognitive Learning ProcessesIntelligent Tutoring Systems and Adaptive LearningLearning Styles and Cognitive Differences

The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index; none of the 12 sources its claims cite is checked for support yet.

A Personalization Effect in Multimedia Learning: Students Learn Better When Words Are in Conversational Style Rather Than Formal Style.

Mayer, Richard E., Fennell, Sherry, Farmer, Lindsay, Campbell, Julie·2004·Journal of Educational Psychology

Abstract

Students received a personalized or nonpersonalized version of a narrated animation explaining how the human respiratory system works. The narration for the nonpersonalized version was in formal style, whereas the narration for the personalized version was in conversational style in which “the ” was changed to “your ” in 12 places. In 3 experiments, students who received the personalized version scored significantly higher on transfer tests but not on retention tests than did students who received the nonpersonalized version. The results are consistent with a cognitive theory of multimedia learning in which personalization causes students to actively process the incoming material. Suppose you are sitting at your computer, exploring a Web site on health information. You click on a link about how the human respiratory system works, and you see a short presentation on the screen. The presentation consists of an animation depicting the processes of inhaling air into the lungs, exchanging oxygen from the lungs into the bloodstream and carbon dioxide from the blood-stream into the lungs, and exhaling air out of the body. The presentation also consists of a corresponding narration spoken in a

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

Across three experiments, college students who learned from a narrated animation about the respiratory system with conversational wording (“your” instead of “the” in 12 places) performed better on transfer tests than students who heard formal wording, but not on retention tests. The authors interpret this personalization effect as evidence that conversational style prompts deeper processing of multimedia material.

Key findings

  • In Experiment 1, the personalized group scored higher on transfer than the nonpersonalized group (M = 7.1, SD = 2.4 vs. M = 6.0, SD = 1.8), t(60) = 2.170, p = .034, effect size = 0.65; retention did not differ significantly (both M = 11.3; effect size = −0.02).
  • In Experiment 2, the personalized group again scored higher on transfer (M = 7.8, SD = 2.4 vs. M = 5.6, SD = 2.0), t(25) = 2.516, p = .019, effect size = 1.07; retention did not differ significantly (M = 8.2 vs. M = 9.0; effect size = −0.21).
  • In Experiment 3, the personalized group scored higher on transfer (M = 6.2, SD = 2.0 vs. M = 4.5, SD = 2.3), t(30) = 2.177, p = .037, effect size = 0.72; retention did not differ significantly (M = 11.1 vs. M = 9.6; effect size = 0.37).
  • Interest measures did not show a statistically significant personalization effect: in Experiment 3, interest ratings were M = 5.1 vs. M = 4.5, t(30) = 1.56, p = .129, effect size = 0.55; in Experiment 2, no participants in either group showed facial expressions during learning.

Methods

  • Three experiments used a personalized or nonpersonalized version of a roughly 60-s narrated animation on how the human respiratory system works; the only difference was changing “the” to “your” in 12 places in a 100-word narration spoken in a male voice.
  • Participants were 62 college students in Experiment 1 (29 personalized, 33 nonpersonalized), 27 college students in Experiment 2 (14 personalized, 13 nonpersonalized), and 32 paid adults in Experiment 3 (17 personalized, 15 nonpersonalized).
  • After viewing, participants completed a retention test and five transfer test sheets; retention and transfer were scored out of 20 idea units or acceptable answers by two raters with consensus. Experiment 2 video recorded faces and tallied smiles; Experiment 3 added 1–7 difficulty and interest ratings. Main analyses were t tests with effect sizes.

Limitations

  • The paper states that its interest measures were problematic: smiling in Experiment 2 was insensitive, and the interest rating in Experiment 3 did not reach significance, so either the measures were defective or the interest hypothesis needs revision.
  • The paper states that direct measures of cognitive processing during learning are missing and calls for further work, including possible fMRI measures, to test whether personalization primes deeper processing.
  • The paper notes that spatial ability data in Experiments 1 and 3 were not used because there were not enough participants, and that an additional study similar to Experiment 1 was not reported because of possible data coding errors. Evident from the text: samples were small, participants were from university subject pools, and the lesson was a single short topic, limiting generalizability.

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Integrity signals

Registry

Crossref · 10.1037/0022-0663.96.2.389

Cites

16 of 16 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

0 of 12 cited sources checked · 0 supported · 0 flagged

Show all 25 claims

  • Probably not a substantial claim. 13
  • It may state two separate claims as one. 9
  • The quote only partly states this claim. 1
20 of 20
  • The paper relies on this without support.

    Both the personalized and nonpersonalized groups have adequate cognitive capacity for basic processing of the material and will pay attention to and encode the material.

    “The rationale for this prediction is that both groups have adequate cognitive capacity for basic processing of the material and they both will pay attention to material and encode it”
  • The paper relies on this without support.

    Both the personalized and nonpersonalized groups have adequate cognitive capacity for deeper processing.

    “although both groups also have adequate cognitive capacity for deeper processing”
  • The paper relies on this without support.

    Students in the personalized group will be more likely to use their cognitive capacity for organizing the material and integrating it with prior knowledge because they are more interested in understanding the material.

    “students in the personalized group will be more likely to use that capacity for organizing the material and integrating it with prior knowledge because they are more interested in understanding the material.”
  • The paper relies on this without support.

    The cognitive theory of multimedia learning correctly describes that personalization increases the learner's interest, which increases effort and deeper processing, leading to improved transfer performance.

    “One answer to this question comes from the cognitive theory of multimedia learning: Personalization increases the learner's interest, increased interest causes the learner to exert more effort to engage in active cognitive processing during learning, and an increase in active cognitive processing during learning results in deeper learning, which is manifested in improved transfer performance.”
4 of 4

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?

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.

  • Not confirmedt(25) = 0.594reported p = .557 · recomputed p = .558

    “t (25) = 0.594, p = .557”

  • Consistentt(60) = 2.17reported p = .034 · recomputed p = .034

    “t (60) = 2.170, p = .034”

  • Consistentt(25) = 2.516reported p = .019 · recomputed p = .019

    “t (25) = 2.516, p = .019”

  • Consistentt(30) = 1.087reported p = .286 · recomputed p = .286

    “t (30) = 1.087, p = .286”

  • Consistentt(30) = 2.177reported p = .037 · recomputed p = .037

    “t (30) = 2.177, p = .037”

  • Consistentt(30) = 1.56reported p = .129 · recomputed p = .129

    “t (30) = 1.56, p = .129”

  • Consistentt(30) = 0.324reported p = .748 · recomputed p = .748

    “t (30) = 0.324, p = .748”

7 of 7

Self-check

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

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Citations

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Metadata

Authors
Mayer, R. E., Fennell, S., Farmer, L., & Campbell, J.
Affiliations
University of California, Santa Barbara (US)
Venue
Journal of Educational Psychology
Published
2004-06
Volume
96
Issue
2
Pages
389-395
ISSN
  • 0022-0663 (ISSN-L)
  • 1939-2176
OpenAlex
W2096394886
Cited by
298
References
14
Citations by year
2026: 11 · 2025: 13 · 2024: 9 · 2023: 13 · 2022: 11 · 2021: 22 · 2020: 11 · 2019: 17 · 2018: 18 · 2017: 14 · 2016: 13 · 2015: 19 · 2014: 21 · 2013: 22 · 2012: 14
FWCI
8.06
Type
journal article
Language
en
Open access
closed
Locations
Journal of Educational Psychology (publishedVersion)
Topics
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
  • Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
  • Social Sciences › Psychology › Developmental and Educational Psychology › Learning Styles and Cognitive Differences
Keywords
personalization, conversational style, formal style, narrative style, multimedia learning, cognitive theory of multimedia learning, transfer, retention, respiratory system, active processing

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