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Enhancing Mathematics Learning Outcomes for Minority Students Using Social Media
- 1. RESEARCH POSTER PRESENTATION DESIGN © 2012
www.PosterPresentations.com
A majority of young collegiate male and female students lose interest in
mathematical topics within their first two years of study. Some lose interest
because they fail to see the correlation between their course studies and
their long term career goals, for most minority females, a lack of mentoring
plays a big part in their loss of interest in STEM (Science Technology
Mathematics and Engineering) subjects, others struggle due to the rigorous
pace of their STEM courses, and others struggle due to grade inflation
from previous class experiences. Why is it important that we work together
to change the pattern this pattern of disinterest?
1) Because mathematics is the language of science and is the means of
quantitative modeling to describe the physical world.
2) Because strong mathematic skills are a gateway to productive inter-
disciplinary exchanges and quality understanding of STEM subjects.
3) Because mathematics is a critical literacy needed for the United States’
workforce.
This research project will explore enhancing mathematic learning
outcomes, using social-cultural cognition theory to train freshmen minority
college students to develop PLEs (Personal Learning Environments),
leveraging social media tools, and extended learning communities to
enhance their learning capabilities.
ABSTRACT
INTRODUCTION
The PLE approach will help utilize the learning instructional model and the
“whiteboard tradition” will be restored by active communal learning
environments in which different incorporate theories & principles, which
also can help students excel in the process of examination for existing
problems in innovative & unique ways to utilize their mathematical
knowledge for weekly discussions. The students will be matched in groups
from 3-5 with their peers each week during lectures, they all have the
ability to share notes and all learn effectively & actively from each other.
They will be required to present the group’s understanding or the
knowledge obtained from the previous lesson of that week. Homework
assignments are replaced with these courses within the weekly
experimental mathematics analysis project. It will be interdisciplinary-
based for students and they are required to complete a project topic
selected by their instructor.
METHODS AND DATA
Twitter’s popularity as an information source has led numerous
communities utilizing it in various domains including Humanitarian
Assistance, Disaster Relief to provide situational awareness to a crisis
situation. Researchers have used Twitter to predict the occurrence of
earthquakes and identify relevant users to follow to obtain disaster related
information [18-22]. Twitter is many things to many people, for
mathematics instruction at UAPB is a tool to exploit student engagement
of minorities.
PRELIMINARY FINDINGS
IMPLICATIONS
This better helps students to engage in their learning environment while
being social and engaging in an overall better class lecture. It also gives
students better opportunities to learn in a more digital and graphic forms of
mathematics rather the standard white-board, method of teaching. Students
also have a more reliable way of relation to the lectures given each day.
REFERENCES
[1] A. L. Griffith, "Persistence of women and minorities in STEM field
majors: Is it the school that matters?," Economics of Education Review,
vol. 29, pp. 911-922, 2010.
[2] A. V. Maltese and R. H. Tai, "Pipeline persistence: Examining the
association of educational experiences with earned degrees in STEM
among US students," Science Education, vol. 95, pp. 877-907, 2011.
[3] K. A. Smith, T. C. Douglas, and M. F. Cox, "Supportive teaching and
learning strategies in STEM education," New Directions for Teaching and
Learning, vol. 2009, pp. 19-32, 2009.
[4] R. G. Ehrenberg, "Analyzing the factors that influence persistence
rates in STEM field, majors: Introduction to the symposium," Economics
of Education Review, vol. 29, pp. 888-891, 2010.
[5] T. Dreyfus, "Why Johnny can't prove," Educational studies in
mathematics, vol. 38, pp. 85-109, 1999.
[6] C. Williams, O. Akinsiku, C. Walkington, J. Cooper, A. Ellis, C.
Kalish, et al., "Understanding students’ similarity and typicality judgments
in and out of mathematics," in Proceedings of the 32nd annual meeting of
the North American Chapter of the International Group for the Psychology
of Mathematics Education, 2011.
[7] P. T. Terenzini, L. Springer, P. M. Yaeger, E. T. Pascarella, and A. Nora,
"First- generation college students: Characteristics, experiences, and
cognitive development," Research in Higher education, vol. 37, pp. 1-22,
1996.
[8] E. T. Pascarella, C. T. Pierson, G. C. Wolniak, and P. T. Terenzini,
"First- generation college students: Additional evidence on college
experiences and outcomes," Journal of Higher Education, pp. 249-284,
2004.
[9] T. C. Gilmer, "An understanding of the improved grades, retention and
graduation rates of STEM majors at the Academic Investment in Math and
Science (AIMS) Program of Bowling Green State University (BGSU),"
Journal of STEM Education, vol. 8, pp. 11-21, 2007.
[10] K. Eagan, F. Herrera, J. Sharkness, S. Hurtado, and M. Chang,
"Crashing the gate: identifying alternative measures of student learning in
introductory science, technology, engineering, and mathematics courses,"
American Research in Education Association, New Orleans, Louisiana,
USA, 2011.
[11] X. Chen, "STEM Attrition: College Students' Paths into and out of
STEM Fields. Statistical Analysis Report. NCES 2014-001," National
Center for Education Statistics, 2013.
AKNOWLEDGEMENTS
[12] J. S. Hyde and J. E. Mertz, "Gender, culture, and mathematics
performance," Proceedings of the National Academy of Sciences, vol. 106,
pp. 8801-8807, 2009.
[13] J. G. Stout, N. Dasgupta, M. Hunsinger, and M. A. McManus,
"STEMing the tide: Using ingroup experts to inoculate women's self-
concept in science, technology, engineering, and mathematics (STEM),"
Journal of personality and social psychology, vol. 100, p. 255, 2011.
[14] J. Fairweather, "Linking evidence and promising practices in science,
technology, engineering, and mathematics (STEM) undergraduate
education," Board of Science Education, National Research Council, The
National Academies, Washington, DC, 2008.
[15] R. McCartney and K. Sanders, "First-year students' social networks:
learning computing with others," in Proceedings of the 14th Koli Calling
International Conference on Computing Education Research, 2014, pp.
159-163.
[16] J. Tenenberg and M. Knobelsdorf, "Out of our minds: a review of
sociocultural cognition theory," Computer Science Education, vol. 24, pp.
1-24, 2014.
[17] L. P. Steffe, P. Nesher, P. Cobb, B. Sriraman, and B. Greer, Theories
of mathematical learning: Routledge, 2013.
[18] M. Berger, "Vygotsky’s theory of concept formation and mathematics
education," in Proceedings of the 29th Conference of the International
Group for the Psychology of Mathematics Education, Bergen, Norway,
2005, pp. 153-160.
[19] I. A. Zualkernan, "Using Soloman-Felder Learning Style Index to
Evaluate Pedagogical Resources for Introductory Programming Classes,"
presented at the Proceedings of the 29th international conference on
Software Engineering, 2007.
[20] A. T. Chamillard and R. E. Sward, "Learning styles across the
curriculum," presented at the Proceedings of the 10th annual SIGCSE
conference on Innovation and technology in computer science education,
Caparica, Portugal, 2005.
[21] N. S. Grant, "A study on critical thinking, cognitive learning style,
and gender in various information science programming classes,"
presented at the Proceedings of the 4th conference on Information
technology curriculum, Lafayette, Indiana, USA, 2003.
[22] V. C. Galpin, I. D. Sanders, and P.-y. Chen, "Learning styles and
personality types of computer science students at a South African
university," presented at the Proceedings of the 12th annual SIGCSE
conference on Innovation and technology in computer science education,
Dundee, Scotland, 2007.
This project is housed at the University of Arkansas at Pine Bluff (UAPB),
a student-focused Historically Black College and University (HBCU),
within the Department of Mathematics and Computer Science.
Mathematics is a major bottleneck for many students that enter the
university. For many incoming first-generation minority college students
there is a cognitive conflict that student’s experience in which many of the
mathematic skills they learned in their K-12 training, contradict the
mathematics practices expected at the university level. According to
Dreyfus [1-2], and other researchers many of these students suffer from a
cognitive gap, in which when the students are confronted with new
knowledge, which conflicts with pervious knowledge, a cognitive conflict
is created. Mathematic courses are still bottleneck courses for many
students matriculating at UAPB. Courses are still are taught in isolation
from the other disciplines, using standard lecture style presentations and
instructors overlook the natural connections with other disciplines such as,
Physics, Chemistry, Biology, Computer Science, and Engineering. For
instance, the typical incoming freshmen at UAPB, has an ACT score of
15~19, and enrolls in remedial mathematics course:
• Math 1310 Elementary Algebra (STEM major)
• Math 1359 Enhance Quantitative Literacy (Non-STEM).
Very few incoming freshmen score the required ACT score of 19 to enter
directly into Math 1330 College Algebra or Math 1550 Precalculus, which
is designed to allow students to investigate, and apply general function
properties with algebraic mathematics and trigonometric functions to solve
mathematical problems. As a result students typical mathematics
matriculation at UAPB requires four semesters on average rather the two
semesters required for non-STEM, three for STEM majors. Many first-
generate minority STEM majors are ill prepared in mathematics resulting
in a low retention within disciplines in the first two years of study.
Therefore, our approach is to train students leverage cultural frameworks
they are already familiar with composed of:
(1) Communal learning via experiential mathematic analysis.
(2) Communal learning via social media micro-blogging.
(3) Problem modeling via tangible daily tasks.
Dr. Karl Walker, Robin Ghosh, Leonardo Vieira, Chirone Gamble Jr,
Adrian Thompson, Javaughn Love, Xavier Graves, Tiffany Howell
Mathematics Personal Learning Environments, Leveraging
Social Media and Self-Regulated Learning
Project Title: Mathematics STEM Undergraduate Apprentice
Program
Award Number: P120A150078
Funding Agency: US Department of Education
Project Coordinator: Robin Ghosh
Figure 1: Clustering of students around a given mathematics
topic.
Figure 2: Representation of centrality gives us the idea of who is
the most important person on a network.