Effects of an Online Instructional Application on Reading And Mathematics Standardized Test Scores

Martindale, Trey; Pearson, Carolyn; Curda, L. K.; Pilcher, Janet K.

doi:10.1080/15391523.2005.10782442

Cited by 21 publications

(16 citation statements)

References 9 publications

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“…A computer-based activity aimed at improving test-taking techniques may be effective with pupils struggling with such techniques; so, a sample consisting of these pupils may show a larger (raw) difference in mean scores on a suitable test. The same activity may be ineffective with confident test takers; so, a sample of those may show little difference in mean scores (Martindale et al, 2005).…”

Section: Effect Size At the Study Levelmentioning

confidence: 99%

Princesses are bigger than elephants: Effect size as a category error in evidence‐based education

Simpson

2018

British Educational Res J

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Much of the evidential basis for recent policy decisions is grounded in effect size: the standardised mean difference in outcome scores between a study's intervention and comparison groups. This is interpreted as measuring educational influence, importance or effectiveness of the intervention. This article shows this is a category error at two levels. At the individual study level, the intervention plays only a partial role in effect size, so treating effect size as a measure of the intervention is a mistake. At the meta‐analytic level, the assumptions needed for a valid comparison of the relative effectiveness of interventions on the basis of relative effect size are absurd. While effect size continues to have a role in research design, as a measure of the clarity of a study, policy makers should recognise the lack of a valid role for it in practical decision‐making.

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Section: Effect Size At the Study Levelmentioning

confidence: 99%

Princesses are bigger than elephants: Effect size as a category error in evidence‐based education

Simpson

2018

British Educational Res J

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“…Drawing this section to a close, we note that with only one or two exceptions (eg, Hagerty & Smith, 2005; McSweeney & Weiss, 2003) previous studies of regular online assessment tools have been hampered by small sample sizes (eg, Li & Edmonds, 2005), confounding effects such as type selection bias (eg, Henly, 2003; Kibble, 2007; Stillson & Alsup, 2003) or high variance in instrument exposure (eg, Martindale et al , 2005). Despite this, the literature seems willing to suggest at the least a neutral outcome with respect to online formative (or low‐mark summative) assessment, and in the most detailed analytical work, a better than neutral outcome.…”

Section: Related Studiesmentioning

confidence: 99%

“…Of course, within the simple category of 'online assessment', the wide variety of approaches makes comparison difficult. Martindale, Pearson, Curda and Pilcher (2005) conduct an analysis of the locality specific Florida Comprehensive Assessment Test (FCAT) Explorer program, an online formative testing resource for students in the Florida jurisdiction. The study compares schools in the jurisdiction that used the FCAT Explorer software with similar schools (eg, by district, size, performance) that did not.…”

Section: Related Studiesmentioning

confidence: 99%

Does regular online testing enhance student learning in the numerical sciences? Robust evidence from a large data set

Angus

Watson

2009

Brit J Educational Tech

132

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In recent years, online tools have increasingly contributed to both course delivery and assessment across various domains with mixed quantitative results. We examine the introduction of a regular online assessment tool ('e-quiz') delivered by the WebCT Vista content management system to a large first-year quantitative methods course at UNSW, Sydney (Australia). Unique aspects of this study include the quantitative (mathematical) nature of the online learning, the larger than usual sample size (n > 1500 in toto), the inclusion of several difficult-to-obtain explanatory variables, and the high diversity in sub-population attributes. We principally measure the effectiveness of the e-quiz tool from the perspective of student performance in an end of semester closed-book examination. We also consider student opinions and attitudes to the introduction of the online tool. Data taken on attendance at voluntary peerassisted learning classes, used as a proxy for student effort, along with pre-enrolment mathematical aptitude data are used to identify the specific contribution of the e-quiz tool to student learning. We find support for the hypothesis that regular usage of online learning tools (not grade) significantly and positively contributes to student performance. Furthermore, we find that the hypothesis that this improvement is due mainly to improving student feedback is supported by an analysis of student surveys. Finally, in an extension, we consider the use of such low-cost, online quizzes as a possible identifier for 'at-risk' students.

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“…Also, supplemental digital resources may have limited effects on student subpopulations, such as underperforming students and English language learners (Rutherford et al, 2014). Moreover, perceptions related to the benefits and value of supplemental digital resources among teachers may influence how they implement and use these resources with students (Martindale, Pearson, Curda, & Pilcher, 2005).…”

Section: Impact Of a Web-based Adaptive Supplemental Digital Resourcementioning

confidence: 99%

Impact of a Web-Based Adaptive Supplemental Digital Resource on Student Mathematics Performance

Sharp

Hamil²

2018

OLJ

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Much literature has presented evidence that supplemental digital resources enhance student performance with mathematics. The purpose of this study was to explore the impact of a web-adaptive digital resource, Think Through Math©, on student performance with state-mandated annual standardized mathematics assessments. This study utilized a quantitative research design and conducted multiple regression analyses among 723 students from a north Texas school district that showed high-levels of use with Think Through Math© during the 2015-2016 school year. Data from Think Through Math© reports and annual standardized mathematics assessments were collected and analyzed from elementary, intermediate, junior high, and high school campus levels. Results of the multiple regression analyses were reported for each campus level, as well as several statistically significant and positive associations.

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Effects of an Online Instructional Application on Reading And Mathematics Standardized Test Scores

Cited by 21 publications

References 9 publications

Princesses are bigger than elephants: Effect size as a category error in evidence‐based education

Princesses are bigger than elephants: Effect size as a category error in evidence‐based education

Does regular online testing enhance student learning in the numerical sciences? Robust evidence from a large data set

Impact of a Web-Based Adaptive Supplemental Digital Resource on Student Mathematics Performance

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