Technology + Pedagogy Guide: Bringing Method to the Madness

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Shaunna Smith, Ed.D.

Dr. Smith is an Assistant Professor of Educational Technology in the Department of Curriculum and Instruction at Texas State University. Her research interests focus on technology integration strategies within K–12 and post-secondary learning environments. As a former secondary art teacher, she is particularly interested in exploring how the hands-on use of design-based technologies (e.g., digital fabrication, 3D modeling and printing, computer programming, and robotics) can impact multidisciplinary learning that transcends traditional content contexts. At her mobile makerspace, The MAKE Lab, she is currently researching how recurring experiences with these design-based technologies impact self-efficacy and positive attitudes toward failure (e.g., grit and persistence in the face of obstacles; reconceptualization of failure as a paradigm for creative learning) with teachers and K–12 students.

It is easy for educators to get lost in the madness of the overwhelming number of instructional options and technology tools available today. If we aren’t careful, we can easily become the Alice who falls down the rabbit hole into a technology wonderland, quickly becoming enamored and sidetracked with every tool as they get “curiouser and curiouser,” discouraged by the Mad Hatter who suggests a new approach to everything we’ve been doing, or frightened by the Queen of Hearts who suggests that change is unwelcome. As educators, our time is precious, and we need to be mindful of our productivity; however, we also need to learn how to leverage our own individualized knowledge and easily accessible technology in order to enhance our instruction and student learning potential.

Although published before digital technology was commonplace in education, Shulman’s (1987) theories of “pedagogical reasoning” and “pedagogical content knowledge” remind us that a teacher must remain focused on their instructional intent and interconnectedness to subject matter. Mishra and Koehler’s (2006) Technological Pedagogical Content Knowledge (TPACK) draws upon Shulman’s theories by adding considerations of technological knowledge and its connections to pedagogical knowledge and content knowledge, thus creating a context for discussing the new complexities of considerations that teachers must contend with. Content connections are found relatively easily with textbook companion websites and the like; however, making a meaningful connection between technology and pedagogy can be a little bit more complicated.

Designed as a helpful decision-making tool, the Technology + Pedagogy Guide can aid educators in instructional planning of activities that integrate instructionally appropriate technology tools to support a variety of learning contexts (the complete Technology + Pedagogy guide is available at: https://tinyurl.com/techology-pedagogy). Table 1 shows how it organizes commonly accessible and free technology tools into categories related to their essential characteristics (tool affordances) and ability to align with Bloom’s Revised Taxonomy (Krathwohl, 2002) to support student-centered learning objectives:

TECHNOLOGY CATEGORIES ESSENTIAL CHARACTERISTICS

(Tool Affordances and Instructional Purpose)

CONNECTIONS TO BLOOM’S TAXONOMY LEVELS

(Learning Objectives)

Acquisition & Investigation Tools Technology tools that allow users to capture and collect information. Remembering
Presentation & Remixing Tools Technology tools that allow users to demonstrate understanding of concepts through original expression or through remixing (editing existing content by putting a new ‘spin’ on it). Understanding

Applying

Discussion & Reflection Tools Technology tools that allow users to communicate ideas and experiences with self and/or others. Analyzing

Evaluating

Creation & Editing Tools Technology tools that allow users to generate original artifacts to demonstrate personally meaningful knowledge. Creating


Acquisition and Investigation tools
assist learners in capturing and collecting information, which is appropriate for instructional goals that align with the lower-level Bloom’s Revised Taxonomy levels of Remembering. This category of tool is perfect for the beginning stages of research projects when you want students to capture and collect information related to a topic. Leveraging digital functionality, students can use these technology tools to complete individual assignments or to co-construct as a collaborative group, with the added benefit of even being able to communicate across time and space — beyond the four walls of your classroom.

Presentation and Remixing tools assist learners in demonstrating their understanding of concepts through altering existing content and application of concepts through presenting information to others. This category is appropriate for instructional goals that align with the Bloom’s Revised Taxonomy levels of Understanding and Applying. This category of tool is perfect for brainstorming ideas and organizing concepts or presenting proposals to the class. Leveraging digital functionality, these tools can easily be worked on outside of class and can be shared with others through using URL links.

Discussion and Reflection tools assist learners in communicating ideas and experiences to themselves and/or others. This category is appropriate for instructional goals that align with the middle levels of Bloom’s Revised Taxonomy levels for Analyzing and Evaluating. This category of tool can be used to inspire diverse perspectives throughout an on-going learning module or project, as well as a culminating reflection to examine personal learning at the end of the semester. Leveraging digital functionality, these tools can easily take advantage of the ability to “comment” and “reply” to student posts as well as share URL links of creations to spark further dialogue.

Creation and Editing tools assist learners in generating original artifacts to demonstrate their own personally meaningful knowledge. This category is appropriate for instructional goals that align with the highest levels of Bloom’s Revised Taxonomy levels for Creating. This category of tool can be used to support smaller scale creative activities throughout a module or can be expanded to allow students to explore open-ended original artifact creation. Leveraging digital functionality, these tools can easily take advantage of the wide variety of free tools that can allow students to create a wide variety of media (i.e. photo editing, videography, 3D modeling, computer programming) but also easily share online with others.

Conclusion

Given the right level of support, even technology novices who are overwhelmed by the initial madness of this technology wonderland can transition into becoming confident and effective technology integrators who can select tools to amplify and transform their teaching. Through using the Technology + Pedagogy Guide, educators can focus on student-centered pedagogies by recognizing the categorical affordances and characteristics of the tools. In doing so, educators can develop a more richly constructed transference of knowledge by having an essential understanding of what qualities to look for in the ever-changing palette of technology tools in order to match pedagogical goals that will remain relevant as the technologies continue to evolve.

References

Krathwohl, D. R. (2002). A revision of bloom’s taxonomy: An overview. Theory into Practice, 41(4), 212.

Mishra, P., & Koehler, M. (2006). Technological pedagogical content knowledge: A framework for integrating technology in teacher knowledge. Teachers College Record, 108(6), 1017-1054.

Shulman, L. S. (1987). Knowledge and teaching: Foundations of the new reform. Harvard Educational Review, 57, 1-22.

Overcoming Mathematics and Testing Anxiety with Research-Based Strategies

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Theresa Hoang and Darolyn Flaggs

Theresa Hoang is a Ph.D. student in the Developmental Education program at Texas State University with a specialization in developmental math.  Previously, she earned her M.A. from the same program with a concentration in literacy.  She has taught learning frameworks at the college level and mathematics at the high school, and she has assisted in teaching developmental reading and developmental mathematics at Texas State University.  Her research interests include motivation of underprepared students in higher education and social psychological interventions.

Darolyn Flaggs is a Ph.D. student in the Developmental Education Program at Texas State University with a specialization in Developmental Mathematics. She received her B.S. in Mathematics at Texas Southern University and her M.Ed. in Mathematics Education at Texas State University. Her research interests include studying historically underrepresented student populations within the mathematics setting and exploring variables affecting student’s persistence to degree completion. Ms. Flaggs has taught undergraduate mathematics courses, been involved in the revision of the developmental mathematics scope and sequence, and lesson plans, and worked with FOCUS and SLAC at Texas State University. She is currently working under the research mentorship of Dr. Taylor Acee in the Department of Curriculum and Instruction.

How does mathematics and testing anxiety affect your students?  As doctoral students teaching developmental mathematics for the first time, we quickly realized the extent to which mathematics and testing anxiety was hurting our students’ academic outcomes.  During office hours, students often self-proclaimed to having anxiety about test-taking and about mathematics in general.  While not all students explicitly told us about their worries, it was sometimes intuitively clear that they struggled with mathematics and testing anxiety.  These common occurrences led us to explore deeper into what was causing students to have feelings of anxiety and what could we do as mathematics educators to help our students in these situations.

While searching through the literature, we found an incredible useful journal article that we would like to share with you entitled “Anxiety and Cognition” and written by Maloney, Sattizahn, and Beilock (2004).  In this article, Maloney et al. (2014) described how mathematics and testing anxiety affected the brain; anxiety can cause maladaptive physical responses and negative thoughts, which can take up prefrontal cortical resources and working memory that could otherwise be used for mathematics.  To combat these effects in the brain, Maloney et al. (2014) identified key strategies across a plethora of anxiety research.  These primary strategies included expressive writing (Park, Ramirez, & Beilock, 2014), arousal reappraisal (Jamieson, Mendes, Blackstock, & Schmader, 2010), stereotype threat reappraisal (Johns, Schmader, & Martens, 2005), and breathing exercises (Brunye, Mahoney, Giles, Rapp, Taylor, & Kanarek, 2013).  While in-depth information about each strategy can be found in Maloney et al.’s (2014) article, the following list will provide brief descriptions of how to implement each strategy:

  • Expressive Writing: Immediately before students take an exam, ask students to write about their feelings about the upcoming exam for 10 minutes. The goal of this activity is for students to express their negative thoughts and worries before the exam so that during the exam, students can use their working memory to think about their math problems instead of their anxieties.
  • Arousal Reappraisal: Students who perform well on tests regardless of their anxiety tend to look at stress-inducing situations as a challenge instead of a threat. So, when students begin to feel their heart rate increasing or their body sweating because of a stress-inducing situation, encourage students to interpret those signs of arousal as normal physiological responses to a challenge and that these signs can actually help with performance rather than hurt it.
  • Stereotype Threat Reappraisal: This strategy is useful for groups of people, such as women or students of color, who may experience stereotype threat, which is “the fear of acting in such a way that confirms a negative stereotype about a group to which one belongs” (Maloney et al., 2014, p. 408). Informing these students about the existence of stereotype threat and the possibility of anxiety arising from stereotype threat can help students assess why they feel anxious and perform better on exams.
  • Breathing Exercises: Encouraging students to engage in focused breathing exercises before exams, similar to the one found here, can increase student performance. By completing the breathing exercises before exams, students may be able to focus their attention better and free up cognitive resources to use during exams.

Over the past few decades, the role of developmental mathematics instructors have evolved; not only do instructors play a key role in facilitating the growth of student knowledge in mathematics, but effective instructors also address non-academic factors, such as motivation and anxiety, to further increase their students’ success.  By learning and practicing these research-based strategies proven to help students with mathematics and testing anxiety, instructors have the golden opportunity to positively impact student success.

Reference

Maloney, E. A., Sattizahn, J. R., & Beilock, S. L. (2014). Anxiety and cognition. WIREs Cognitive Science, 5(4), 403-411.

 

 

How to Contextualize Math Using Infographics

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Patricia Helmuth

Patricia Helmuth is an Adult Numeracy Consultant and Educator. She teaches two HSE classes, does one-on-one tutoring (in partnership with the Center for Workforce Development), and is a Professional Development Team Member for the Adult Program at Sullivan County BOCES, NY. In addition to working with students, she enjoys sharing her “numeracy adventures” at the regional, state, and national level by presenting at conferences and writing for adult education web-based resources. She currently serves as the newsletter editor for The Adult Numeracy Network.

In a traditional math classroom, where math topics may be taught in isolation, students watch the instructor model a procedure on the board and then students are expected to memorize, repeat, and practice the procedure. The trouble is, many students have difficulty connecting the procedure to real-life applications. This disconnect that students experience is evidenced in ABE/HSE classes, as well as on college campuses in developmental math classes. According to Models of Contextualization in Developmental and Adult Basic Education, “…students who want to be nurses, EMTs, firemen…. are stuck in a course that doesn’t work.” Conversely, when math is contextualized, students can develop conceptual understanding of the math.  “Research supports the fact that students understand math better when it is contextualized. It motivates and increases the students’ willingness to engage (Tabach & Friedlander, 2008) and provides concrete meaning to the math (Heid et all, 1995).” – (2015 Center for Energy Workforce Development)

In light of this research, and the implementation of the Common Core State Standards and the release of the Workforce Innovation and Opportunity Act, adult education instructors are being called upon to make changes in classroom practice that will adequately prepare students to pass new high-stakes exams and enter college and the workforce with marketable skills. How can adult educators do all this given the short amount of time that adults typically spend in class?

A great place to start is by using a variety of authentic infographics that connect to the social studies, science, or career readiness that you are already teaching. By using infographics, you are combining content knowledge, math skills, and analyzing and interpreting graphic information into one lesson! While infographics may be new to some of us in adult education, they are not new to our students. They see them all the time in the real world so it is imperative that they develop skills to decode them. Besides all that, they are fun! Students are drawn into a conversation when you display an infographic and simply ask:

  • What do you notice? What do you wonder?

Students at all ability levels can participate in a lesson that is introduced like this. Furthermore, when students share out their observations and questions it serves as a formative assessment and enables the instructor to connect what students already know with the whatever math concept the instructor has in mind to draw out of the infographic.

For specific lesson plans and ideas on how to do this, go to:

In the Adult Education classroom today, we need to do more than present our students with workbooks that include traditional examples of maps, charts, and graphs.  We need to use what our students see all around them every day: infographics.

References

Center for Energy Workforce Development (2015). Contextualized math for the energy industry. Retrieved from http://www.cewd.org/contextualized-math/

Education Development Center (EDC). (2012). Models of Contextualization in Developmental and Adult Basic Education. Retrieved from EDC website: http://bit.ly/1KAnllT

 

Program Improvement in Adult Education through Professionalization

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David Borden

David Borden, dborden@austincc.edu, currently works at Austin Community College as the Director of the Career Accelerator, a program dedicated to moving non-traditional students through career pathways–associate degree programs faster and with more supports. He holds a Master’s Degree from UNT. He has taught and managed programs in the U.S. and abroad. This article is adapted from a forthcoming book titled, Unrig the Game: A Proven, Systematic Approach to Successful College Transitions for Adult and Developmental Education Students, with co-author, Charlene Gill.

Payne et al. (2012) show that full-time Adult Basic Education instructors achieve better student performance results than part-time instructors. Unfortunately, very few program directors believe they can afford the expense of hiring full-time instructors. During my nine year tenure as the adult education director at ACC, I oversaw the increase of salaried instructors with health insurance and retirement increase from 9 to 22. During that period, we made significant investments in instructor salary and benefits, but also witnessed significant enrollment increases and performance improvements.

I believe the path to professionalizing the industry is not found in low pay and/or encouraging regions to use more volunteers. Rather, the path is by providing teachers with stable employment, health insurance, retirement plans, and sustained and systematic professional development; by engaging them in decision-making; and by moving away from a seniority system to one that rewards excellence in teaching.

Raising teacher salaries is a long term solution that is difficult to implement in the short term. In our case, salaried instructors cost 30% – 50% more than hourly instructors when you factor in health insurance and retirement plans. This expense can be hard on a limited grant budget, and impossible on a small budget. We have a large enough program (about 4,000 students served per year) that I could find places to reallocate resources. I shut down classes with low enrollment, even with long-standing, high-profile partners that didn’t appreciate being sacrificed for the greater good. Every four classes closed generated a twenty-hour-a-week, salaried instructor with full benefits. Average class sizes grew, but we still capped enrollment at 20 per class.

This strategy created a core faculty that often accrue between 30 and 50 hours of professional development per year. These faculty are engaged in curriculum development, mentoring hourly instructors, and leading workshops. Over the years, hourly and salaried instructors have seen our commitment to them, and they have returned that commitment to the program. These changes have increased our ability to recruit teachers because salaries are more competitive with staff jobs at the college; thus, our ratio of teachers with master’s degrees has doubled. In addition, we’ve reduced costs associated with attrition and training.

In conclusion, we only hire the highest quality instructors into the core faculty. We do not follow a seniority system, but rather look to fill these positions with teachers who not only are effective with students, but also demonstrate a belief in the mission of the division by collaborating well with their colleagues to make considerable contributions.

References

Payne, E.M., Reardon, R.F., Janysek, D.M., Lorenz, M., Lampi, J.P. (2012). Impact on student performance: Texas Adult Education Teacher Credential Study preliminary results. Report for The Texas Adult Education Credential Project, Texas State University

 

Beyond Pro and Con: Re-thinking MOOCs

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William J. Barry

While pursuing his research interests, which include effective technology use, especially among students in transition, William J. Barry teaches developmental reading at St. Edward’s University.  He also trains adult educators in partnership with the Texas Center for the Advancement of Literacy and Learning (TCALL), and teaches first-year seminar at Texas State University, where he is a PhD candidate in developmental education.

Questions of access and affordability remain at the heart of the developmental education discussion (Braun, 2016; Floyd, Felsher, & Ramdin, 2016), and as the results of Moore’s Law continue to bring the world increasingly powerful technology, stakeholders turn to ones and zeroes for answers.  Massive Open Online Courses (MOOCs) represent one such proposal enjoying ample coverage in the literature (e.g., Bastedo, 2016; McClure, 2016).  Advocates say MOOCs increase the accessibility of high-quality education while decreasing the costs (Carey, 2012; Teo, 2015), and critics point to the low academic rigor of MOOCs, while suggesting they profit at the expense of faculty and students (Axmann & Atkins, 2016; Marshall, 2014).

Despite this crucial debate, MOOC critiques rarely consider college students’ perceptions and attitudes.  While administrators, faculty, and media argue apace, it remains unclear how students view MOOCs.  As an educator in the developmental space, I consider students the primary stakeholders.  As such, I expect MOOC policy to benefit students first.  I expect researchers and faculty interested in MOOCs to focus on how students perceive these issues.  After all, their education faces significant transformation in the face of widespread MOOC implementation.

Such expectations drew my attention to a recent study (Cole & Timmerman, 2015), which examined students’ MOOC perceptions.  Using thematic analysis, Cole and Timmerman (2015) suggested students believe MOOCs hold the potential to augment lifelong learning, even though they serve as inferior alternatives to traditional coursework.  Students made their determinations based on several interesting criteria (see Figure 1), which suggest a deeper appreciation for what works in education.  These kinds of nuanced student responses also suggest the value of asking deeper questions regarding MOOC utility, rather than yielding to seductive pro/con binaries.  Answers to such questions inform decisions with regard to the place of MOOCs in higher education, and those decisions stand to affect each one of us in yet unseen ways.

Figure 1.

bill barrys infograph

Click on image to enlarge.

References

Axmann, M., & Atkins, R. (2016). Online community-based practices for massive open online courses (MOOCs) at Open Universities Australia: A case Study. User-Centered Design Strategies for Massive Open Online Courses (MOOCs), 83.

Bastedo, M. N. (2016). American higher education in the twenty-first century: Social, political, and economic challenges. Baltimore, MD: JHU Press.

Braun, H. (2016). The dynamics of opportunity in America: A working framework. In The Dynamics of Opportunity in America (pp. 137-164). New York: Springer International Publishing.

Carey, K. (2012, September 7). Into the future with MOOCs. Chronicle of Higher Education, 59(2), 29.

Cole, A. W., & Timmerman, C. E. (2015). What do current college students think about MOOCs? MERLOT Journal of Online Learning and Teaching, 11, 188-201.

Floyd, D. L., Felsher, R. A., & Ramdin, G. (2016). A retrospective of four decades of community college research. Community College Journal of Research and Practice40(1), 5-22.

Marshall, S. (2014). Exploring the ethical implications of MOOCs. Distance Education, 35, 250-262. doi:10.1080/01587919.2014.917706

McClure, M. W. (2016). Investing in MOOCs: “Frenemy” risk and information quality. In Globalisation and Higher Education Reforms (pp. 77-94). New York: Springer International Publishing.

Teo, T. H. (2015). Just-in-time teaching visual instruction for cohort base interactive learning for engineering course. GSTF Journal on Education (JEd)3(1).