East Meets West, a STEM Research Study
Listen and learn : Research paper
Sunday, November 29, 12:45–1:30 pm PST (Pacific Standard Time)
Dr. Kelly Grogan
As schools and countries address the challenge of preparing young people to understand and participate in today’s highly interdependent and complex world and a future that is largely unpredictable and unknown, a pressing question remains: How do schools manage learning innovation through the implementation of sustainable practices and rigorous research?
|Audience:||Coaches, Teacher education/higher ed faculty, Technology coordinators/facilitators|
|Attendee devices:||Devices not needed|
|Topic:||Assessment/evaluations/use of data|
|ISTE Standards:||For Students:
|Additional detail:||Session recorded for video-on-demand|
Vygotsky’s socio-cultural and social constructivism theory provided the initial theoretical underpinnings for the literature review. Further underpinnings of this study included the substitution, augmentation, modification, redefinition (SAMR) model (Puentedura, 2014), the technology pedagogy content knowledge (TPACK) model (Koehler & Mishra, 2009), and Sieman’s (2005) theory on connectivism. Collectively, these frameworks provided guides to integrate technological, STEAM and pedagogical changes into the classroom with a focus on leveraging 21st-century skills to construct meaning in learning.
The first study is a phenomenological study which involves students who were participating in a STEM summer program co-developed by a Hong Kong based international school and a US based university. The subjects are students who attend international or local schools located in Hong Kong. Up to 200 students each year were invited to participate in the study through surveys. The subjects’ opportunity to participate in the STEM programme is independent of their decision to participate in the research component. The purpose of the study was to identify student interest in STEM Content and Careers. Through collection of survey data after the summer program, the study will identify specific interest in STEM subjects and potential for pursuing STEM as a future career. Participation is voluntary and the subjects were able withdraw from the study at any time.
The second study was a phenomological study focusing on the parents who enrolled their children in the above mentioned STEAM program. This phenomenological study involved parents whose children participated in a STEM summer program co-developed by a Hong Kong based international school and a US based university. The subjects are parents whose children attended international or local schools located in Hong Kong. Up to 200 parents were invited each year to participate in the study through surveys. The subjects’ opportunity for their child/ren to participate in the STEM program was independent of their decision to participate in the
research component. The purpose of the study was to identify parent perceptions around STEM education. Through collection of survey data after the summer program, the study will identify specific attributes of parents perceptions associated with STEM education.
Participation is voluntary and the subjects may withdraw from the study at any time. The research objectives are as follows:
For both studies, the researcher submited open-ended and closed ended questions to subject’s whom have themselves and their legal guardian have signed a consent a form. Subject’s were asked questions about their interest and perception of STEM education and the self-reported impact from participation in the STEM summer program. The subject’s names and school affiliation were not identified in the study. All data has been kept on a password protected computer. A survey questionnaire was used to collect the data. In years 1 and 2 of the study, JOTFORM survey was used. In year 3, survey information was collected on Qualtrics.
Methods of Analysis
The methodology for the student study was a phenomenological study designed to understand students perceptions, perspectives and understandings about STEM learning and 21st-century skills. The methodology for the parent study was a phenomenological study designed to understand parent demographics and their participation in supporting their children academically as well as emotionally and socially. Furthermore, the study captured parent views on math, science and the environment.
Descriptive statistics, including counts and percentages were used to summarize the results for each section of the survey. Bar plots and tables were constructed to visualize the results. In the student study, Cronbach alpha score was used to assess the reliability of the scales for attitudes toward math, science, engineering and technology, 21st century learning skills as well as attitudes towards the future. A Cronbach alpha score greater than 0.7 indicated good reliability of the construct. For each of the five scales, the average score was calculated for each student and the average for each construct was used for various comparisons and correlations. For example, comparisons were made across males and females.
Mean scores were collected for each of the scales after reversing the items previously mentioned. Moreover, paired t-tests were used to compare the mean attitude score towards various subjects while unpaired t-tests were used to compare the mean attitude score for the same subject across males and females. Spearman’s correlation was used to assess the correlation between constructs as well as the correlation of various constructs with age. Analysis was performed using R studio v 3.4. Visualization was performed using ggplot2 and licorice packages. These same methods of analysis will be used for analyze the data from years 2 and 3.
For the parent study, descriptive statistics, including counts and percentages were used to summarize the results for each section of the survey. Analysis was performed using Excel. All data in the survey were categorical data and thus were summarized using counts and percentages.
Study #1- parent results to date
Currently being compiled for years 2 and 3.
The data below is from year 1 of the parent study.
Tables and graphs are not included in this submission.
Table 3 displays the counts and percentages for parent interactions with children at home. The data in table 3 shows that nearly all parents talk and spend time talking with their children (90.5%) and that most of them (88.3%), eat the main meal with their child daily.
In addition, according to table 3, the majority of parents followed math class performance (66.5%) weekly or daily and nearly half followed science class performance, 50.3%. As a contrast to these results, 34.6% of parents obtained math related material every day or once to twice/week and 57% discussed math how math is used everyday. Similarly, 36.8% of parents obtained science related materials on a daily or weekly basis and 76.7% discussed on science is used everyday. The percentage that replied with hardly was highest for follow science performance, 7.3%. Results in table 5 indicate that about 11% of the parents had no competing schools in their area. It may be beneficial to explore the characteristics of these individuals. Data in table 5 demonstrates that 15% of parents had only one competing school and 72.6% had two or more competing schools.The data in table 6 illustrates the most limiting factors for parent participation in school activities were time and not being able to get leave work (32.40% % vs. 30.72%).). Only four parents (2.23%) mentioned that road safety was a hindering factor. Taking care of children at home was the reason for not being able to attend school activities as perceived by 8.38% of the participants. English skills (5.03%) and Cantonese skills (5.03%) were not a limiting factor for most parents. In table 7, distribution of parent responses regarding their views on math and science are provided. As it can be seen, 74.86% of parents strongly agreed that broad science is important to help us to understand the natural world. Following on to this, 74.30% of parents strongly agreed broad science is valuable to society. This is interesting because the students reported low attitudes towards science. Interestingly, 48.6% of parents strongly agreed broad math is important to help understand the natural world. This study set out to assess the perceptions of parents whose child/ren are associated with STEM education in K-12 or equivalent schools. The purpose of the study was to identify parent perceptions around STEM education and the self reported impact for their child/ren who participated in a STEM summer program. The methodology for this study was a phenomenological study designed to understand parent demographics and their participation in supporting their children academically as well as emotionally and socially. Furthermore, the study captured parent views on math, science and the environment.
Study #2- students results to date
The first data set was analyzed and now the analyzation of the other two data sets are underway and will be completed by January 2020.
In the first data set, a total of 114 students completed the survey. Of those, 51 (44.7%) were females and 63 (55.3%) were males. The mean age was 10.6 (Std dev. = 1.7) years. Age was not significantly different across males and females. A mid-study report showed the following results, This study set out to assess the attitudes of students towards various STEM related subjects (math, science and engineering) as well as their attitudes towards 21st century learning and their interest in various future careers. The findings in this study highlighted that half of the students did not have tutors for any subjects and only a small number have tutors for both science and math while the remaining had a tutor for math. Overall results indicated both males and females showed a positive attitude towards all of the scales investigated. Therefore, these findings suggest students attending a summer STEM program had positive attitudes towards Math, Science, Technology and Engineering. Of the constructs analysed, gender was not significantly associated with the mean attitude score towards any of the five scales investigated. However, more males were interested in mathematics and computer science compared to females. On the other hand, more females were interested in veterinary medicine compared to males. Furthermore, attitudes towards engineering and technology was higher than the attitude towards either science or math.
The research benefits parents, teachers and schools’ thinking about or already involved in STEM educational programs. The results of the research identifies parent perceptions regarding STEM education
and self reported impact for their child/ren who participated in a STEM summer program. It also identifies the beliefs and preferences around STEM education from Hong Kong based parents. The research contrasts the findings for STEM percpetions between parents and their children.
Bebell, D., & O’Dwyer, L. M. (2010). Educational outcomes and research from 1:1 computing settings. The Journal of Technology, Learning, and Assessment, 9(1), 5-15.
Clark, W., & Luckin, R. (2013). What the research says. iPads in the classroom. London, England: London Knowledge Lab.
Creswell, J. W. (2015). Educational research: Planning, conducting, and evaluating quantitative and qualitative research (5th ed.). Upper Saddle River, NJ: Pearson Education, Inc.
Cochrane, T. D. (2014). Critical success factors for transforming pedagogy with mobile Web 2.0. British Journal of Educational Technology, 45(1), 65-82.
Dennen, V. P, & Hao, S. (2014). Intentionally mobile pedagogy: The M-COPE framework for mobile learning in higher education. Technology, Pedagogy and Education, 23(3), 397-419. doi:10.1080/1475939X.2014.943278
Fullan, M. (2013). Stratosphere: Integrating technology, pedagogy, and change knowledge. Ontario, CA: Pearson.
Guba, E. (1981). Criteria for assessing the trustworthiness of naturalistic inquiries. Educational Technology Research and Development, 29(2), 75-91.
Koehler, M. J., & Mishra, P. (2009). What is technological pedagogical content knowledge? Contemporary Issues in Technology and Teacher Education, 9(1), 60-70.
Kucher, K., Schamp-Bjerede, T., Kerren, Andreas., Paradis, C., & Sahlgren, M. (2016). Visual analysis of online social media to open up the investigation of stance phenomena. Information Visualization, 15(2), 93-116. doi:10.1177/1473871615575079.
Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33, 159–174.
Miles, M.B., Huberman, A.M., Saldaña, J. (2014). Qualitative data analysis: A methods sourcebook. Thousand Oaks, CA: Sage Publications, Incorporated.
Procedia-Social and Behavioural Sciences, 112, 481-488.
Norris, J. , Ortega, L. & Plonsky, L. (2012). Rick de Graaff and Ute Smit. International Journal of Applied Linguistics, 22, 428-428. doi:10.1111/ijal.12004_3
Puentedura, R. R. (2014). Frameworks for educational technology: SAMR and the edtech quintet, 1-45. Retrieved from
Silge, J. & Robinson, D. (2018). Text mining with r. A tidy approach. Sebastopol: O’Reilly Media.
Vieluf S., Kaplan, D., Klieme, E., & Bayer, S. (2012). Teaching practices and pedagogical innovation: Evidence from TALIS. Paris: OECD Publishing. doi:10.1787/9789264123540-en
Vygotsky, L. S. (1978). Mind in society: The development of higher psychological processes. Cambridge, MA: Harvard University Press.
Zammit, K. (2016). Responding to literature: iPads, apps and multimodal text creation. Literacy Learning: The Middle Years, 24(2), 8.