View in EDS

Quantitative Techniques with Small Sample Sizes: An Educational Summer Camp Example

Saved in:
Bibliographic Details
Title: Quantitative Techniques with Small Sample Sizes: An Educational Summer Camp Example
Language: English
Authors: Trina Johnson Kilty (ORCID 0000-0002-8713-8234), Kevin T. Kilty (ORCID 0000-0002-9768-0676), Andrea C. Burrows Borowczak (ORCID 0000-0001-5925-3596), Mike Borowczak (ORCID 0000-0001-9409-8245)
Source: Problems of Education in the 21st Century. 2024 82(4):507-520.
Availability: Scientia Socialis Ltd. 29 K. Donelaicio Street, LT-78115 Siauliai, Republic of Lithuania. e-mail: scientia@scientiasocialis.lt; e-mail: problemsofeducation@gmail.com; Web site: http://www.scientiasocialis.lt/pec/
Peer Reviewed: Y
Page Count: 14
Publication Date: 2024
Document Type: Journal Articles
Reports - Research
Education Level: High Schools
Secondary Education
Descriptors: Summer Programs, Camps, Computer Science Education, 21st Century Skills, Sample Size, Evaluation Methods, Probability, College Bound Students
ISSN: 1822-7864
2538-7111
Abstract: A computer science camp for pre-collegiate students was operated during the summers of 2022 and 2023. The effect the camp had on attitudes was quantitatively assessed using a survey instrument. However, enrollment at the summer camp was small, which meant the well-known Pearson's Chi-Squared to measure the significance of results was not applied. Thus, a quantitative analysis method using a multinomial probability distribution as a model of a multilevel Likert scale survey was used. Exact calculations of a multinomial probability model with likelihood ratio were performed to quantitatively analyze the results of questionnaires administered to participants in two cohort groups (combined N=17). Probabilities per Likert categories were determined from the data itself using Bayes theorem with a Dirichlet prior. Each cohort functioned as part of a homogenous sample, thus allowing cohorts to be pooled. Post-test revealed significant changes in participants' attitudes after camp completion. Using this technique has implications for studies with small sample sizes. Using exact calculation of the multinomial probability model with the use of likelihood ratio as a statistical test of evidence has advantages: a) it is an exact value that can be used on any size sample, although it offers a quantitative analysis option for small sample size studies; b) depends only on what was observed during a study; c) does not require advanced calculation; d) modern spreadsheet and statistical package programs can calculate the analysis; and e) likelihood ratio employed in Bayes theorem can update prior beliefs according to evidence. Utilizing small sample size quantitative analysis can strengthen insights into data trends and showcase the importance of this quantitative technique.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1435736
Database: ERIC
FullText Text:
  Availability: 0
CustomLinks:
  – Url: https://eric.ed.gov/contentdelivery/servlet/ERICServlet?accno=EJ1435736
    Name: ERIC Full Text
    Category: fullText
    Text: Full Text from ERIC
Header DbId: eric
DbLabel: ERIC
An: EJ1435736
AccessLevel: 3
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Quantitative Techniques with Small Sample Sizes: An Educational Summer Camp Example
– Name: Language
  Label: Language
  Group: Lang
  Data: English
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Trina+Johnson+Kilty%22">Trina Johnson Kilty</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-8713-8234">0000-0002-8713-8234</externalLink>)<br /><searchLink fieldCode="AR" term="%22Kevin+T%2E+Kilty%22">Kevin T. Kilty</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-9768-0676">0000-0002-9768-0676</externalLink>)<br /><searchLink fieldCode="AR" term="%22Andrea+C%2E+Burrows+Borowczak%22">Andrea C. Burrows Borowczak</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-5925-3596">0000-0001-5925-3596</externalLink>)<br /><searchLink fieldCode="AR" term="%22Mike+Borowczak%22">Mike Borowczak</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-9409-8245">0000-0001-9409-8245</externalLink>)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="SO" term="%22Problems+of+Education+in+the+21st+Century%22"><i>Problems of Education in the 21st Century</i></searchLink>. 2024 82(4):507-520.
– Name: Avail
  Label: Availability
  Group: Avail
  Data: Scientia Socialis Ltd. 29 K. Donelaicio Street, LT-78115 Siauliai, Republic of Lithuania. e-mail: scientia@scientiasocialis.lt; e-mail: problemsofeducation@gmail.com; Web site: http://www.scientiasocialis.lt/pec/
– Name: PeerReviewed
  Label: Peer Reviewed
  Group: SrcInfo
  Data: Y
– Name: Pages
  Label: Page Count
  Group: Src
  Data: 14
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2024
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Audience
  Label: Education Level
  Group: Audnce
  Data: <searchLink fieldCode="EL" term="%22High+Schools%22">High Schools</searchLink><br /><searchLink fieldCode="EL" term="%22Secondary+Education%22">Secondary Education</searchLink>
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Summer+Programs%22">Summer Programs</searchLink><br /><searchLink fieldCode="DE" term="%22Camps%22">Camps</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+Science+Education%22">Computer Science Education</searchLink><br /><searchLink fieldCode="DE" term="%2221st+Century+Skills%22">21st Century Skills</searchLink><br /><searchLink fieldCode="DE" term="%22Sample+Size%22">Sample Size</searchLink><br /><searchLink fieldCode="DE" term="%22Evaluation+Methods%22">Evaluation Methods</searchLink><br /><searchLink fieldCode="DE" term="%22Probability%22">Probability</searchLink><br /><searchLink fieldCode="DE" term="%22College+Bound+Students%22">College Bound Students</searchLink>
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 1822-7864<br />2538-7111
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: A computer science camp for pre-collegiate students was operated during the summers of 2022 and 2023. The effect the camp had on attitudes was quantitatively assessed using a survey instrument. However, enrollment at the summer camp was small, which meant the well-known Pearson's Chi-Squared to measure the significance of results was not applied. Thus, a quantitative analysis method using a multinomial probability distribution as a model of a multilevel Likert scale survey was used. Exact calculations of a multinomial probability model with likelihood ratio were performed to quantitatively analyze the results of questionnaires administered to participants in two cohort groups (combined N=17). Probabilities per Likert categories were determined from the data itself using Bayes theorem with a Dirichlet prior. Each cohort functioned as part of a homogenous sample, thus allowing cohorts to be pooled. Post-test revealed significant changes in participants' attitudes after camp completion. Using this technique has implications for studies with small sample sizes. Using exact calculation of the multinomial probability model with the use of likelihood ratio as a statistical test of evidence has advantages: a) it is an exact value that can be used on any size sample, although it offers a quantitative analysis option for small sample size studies; b) depends only on what was observed during a study; c) does not require advanced calculation; d) modern spreadsheet and statistical package programs can calculate the analysis; and e) likelihood ratio employed in Bayes theorem can update prior beliefs according to evidence. Utilizing small sample size quantitative analysis can strengthen insights into data trends and showcase the importance of this quantitative technique.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2024
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1435736
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1435736
RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 14
        StartPage: 507
    Subjects:
      – SubjectFull: Summer Programs
        Type: general
      – SubjectFull: Camps
        Type: general
      – SubjectFull: Computer Science Education
        Type: general
      – SubjectFull: 21st Century Skills
        Type: general
      – SubjectFull: Sample Size
        Type: general
      – SubjectFull: Evaluation Methods
        Type: general
      – SubjectFull: Probability
        Type: general
      – SubjectFull: College Bound Students
        Type: general
    Titles:
      – TitleFull: Quantitative Techniques with Small Sample Sizes: An Educational Summer Camp Example
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Trina Johnson Kilty
      – PersonEntity:
          Name:
            NameFull: Kevin T. Kilty
      – PersonEntity:
          Name:
            NameFull: Andrea C. Burrows Borowczak
      – PersonEntity:
          Name:
            NameFull: Mike Borowczak
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2024
          Identifiers:
            – Type: issn-print
              Value: 1822-7864
            – Type: issn-electronic
              Value: 2538-7111
          Numbering:
            – Type: volume
              Value: 82
            – Type: issue
              Value: 4
          Titles:
            – TitleFull: Problems of Education in the 21st Century
              Type: main
ResultId 1