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Mobile Sensor STEM & EdTech Research: Asking the Right Questions

July 6, 2016

Having been a high school physics, physical science, and engineering teacher myself, I recognize that adoption of new educational technology requires a significant expenditure of time and effort on behalf of both the teachers and the students. What people don't always want to admit is that, truthfully, it's not always worth it. Educators frequently experience a revolving door of new initiatives and new technology that isn't always in the best interests of the students. Educators should be skeptical!

 

Sensors in science education, however, have been backed for years by research-based teaching methods. Do personal, mobile sensors merit the same scrutiny? 

 

There has been a strong emphasis in the physics education community to use mobile sensor technology, and while I absolutely applaud and encourage this, I also realize that adoption of any new teaching tool requires careful consideration by educators. The prime consideration for adoption of any new tool or technique should be evidence-based research (academic research) or teacher engagement in a careful, ongoing analysis of the benefits and drawbacks of its implementation (action research).

 

I'd like to take this particular blog post to analyze some underlying assumptions that are often held in regard to educational technology, and to propose some questions that I don't believe have yet been answered by the educational research community.

 

MOBILE SENSORS AS A CONTEXT FOR TEACHING STEM

Physics education research is one of the most robust educational research fields, and a significant amount of this physics education research has been founded upon what we know about the role of sensors.

 

Mobile sensors are touted as being useful for accomplishing a variety of things, such as collecting data in non-traditional environments (at home, on field trips) and making free data collection tools more widely available at a one-to-one ratio to students.

 

Indeed, mobile sensors can help students to collect data that otherwise would be very hard to collect in order to build an understanding of science concepts (such as the inverse-square law for a point-source of light). Perhaps more importantly, it allows students to engage in research in the way that scientists actually do it in the real world -- the veritable "definition" of inquiry suggested by the AAAS's Project 2061 and the National Research Council's National Science Education Standards and Framework for K-12 Science Education before the invention of the Next Generation Science Standards.

 

It is on this fundamental definition of inquiry that efforts such as Discover Sensors encourages the use of sensors (mobile and non-mobile), and the very wide adoption of commercial sensors in the U.S.

 

EXISTING RESEARCH

However, when looking for academic - or even quantitative - research to support the use of mobile sensors in STEM education, it's not easy to find...if it yet exists at all! The closest I seem to come is when looking at pedagogical techniques that happen to employ technology as a tool in effective instruction. I must include a caveat here: my familiarity is almost exclusively in physics education research (PER), and is therefore probably fairly skewed.

 

There are a number of sensor-heavy approaches in PER that suggest that the use of sensors (typically in the format of academic tools used in a traditional learning context), are beneficial to student learning. An excellent resource for identifying these research-based teaching methods is PhysPort.org. These techniques below are a sampling of the possibilities available to physics teachers:

 

Microcomputer-Based Laboratories

With the advent of data collection tools, Microcomputer-Based Laboratories research looked at the impact of using such tools in the classroom. Microcomputers included technology such as the early use of Texas Instrument calculators with external sensors, and the development of computer interfaces for Vernier and PASCO tools. Significant research in the 1980's demonstrated that data display and analysis tools provided students with:

  • Environmental Simplicity (decreased distractions)

  • Fast Feedback (immediate display and analysis of data for iteration)

  • More Direct Experience (opportunity to measure data that otherwise would be inaccessible)

  • Student Control and Interest (motivation)

  • Ease of Data Transformation (ability to modify display of data)

 

Interactive Lecture Demonstrations

Microcomputer-Based Laboratories continued to look at the use of this technology in a lecture-room format, which engaged students in thought-provoking and sometimes cognitively-dissonant experiences that involved prediction, observation, and analysis.

 

Modeling Instruction

Budding off of efforts to engage students more deeply with data display and analysis, this approach relies heavily on student model-building through data collection. Typically, students identify a system (such as the interaction between net force and acceleration of a system of masses), collect data (such as mass and acceleration), and create models to define the system (such as a graph of mass vs. acceleration and an associated algebraic representation). Although technology was not the central focus of the research used to construct the Modeling Instruction approach, it was a focus of the student engagement, for the very same reasons as those identified in Microcomputer-Based Laboratories.

 

If you are curious about looking at additional pedagogical approaches, check out Tools for Scientific Thinking and Real Time Physics

 

UNANSWERED QUESTIONS

Ultimately, PER is heavily supportive of the use of sensor use in the context of good physics education pedagogy. However, questions remain that deserve attention:

 

  • How do outcomes of teaching physics with personal mobile sensors compare to well-founded research that promote the use of microcomputer-based (typically immobile) sensors?

     

    Does the use of personal mobile devices still result in...

    • ease of data transformation? Or, are mobile sensor apps not yet sufficiently developed to provide robust data transfer or transformation?

    • increased student control and interest? Or, do students feel less motivated to use a tool that is inherently personal and seemingly non-academic?

    • more direct experience? Or, do students find that their personal device, which is highly complex and they do not fully understand, becomes more of a "black box" in the data collection process?

    • the benefits of fast feedback? Or, are mobile sensor apps not yet sufficiently developed to provide robust data analysis capabilities?

    • increased environmental simplicity and decreased distractions? Or, is there a negative effect resulting from accessibility to the Internet, the constant flow of personal messaging, and the relatively "private" sphere of a students' phone that cannot be monitored or controlled by the classroom?

 

Naturally, there are additional questions that remain concerning the cost-time investment-benefit ratio of using any kind of new question, but with so many different tools competing for teachers' and students' attention, here are a few more contextualized questions worth investigating:

  • How should personal mobile sensor be used in coordination with existing commercial sensors? Mobile sensor adoption might be very attractive to a teacher who has no budget and no teaching tools, but a large portion of teachers likely find themselves using mixed technologies. For example, I continued to use Vernier and PASCO sonic rangers for motion detection, force meters to get actual magnitudes of total (not just net) forces, and voltage probes. Smartphone sensors are unlikely to replace any of those pieces of commercial hardware in the near future (without physical add-ons), and some smartphone sensors don't come to stay permanently. The external thermometer, hygrometer, UV, and heart rate sensor all seemed to go in and out of style very quickly!

 

  • How should teachers pedagogically approach technology education versus educational technology? All forms of technology have a learning curve, and how should teachers approach teaching students how to use their personal devices? Beyond ensuring that the technology is accessible to all students, and appropriate for the age and developmental level of the student, safety and liability concerns need to be considered.

 

  • How does the use of personal mobile sensors actually impact gains in:

    • STEM content

    • Science and Engineering Practices

    • Computational Thinking Skills

    • Understandings about the Nature of Science

    • Understandings about the Nature of Technology

    • Positive affect toward careers in STEM

 

  • How can and should mobile sensor technology impact a growing national interest in themes emanating from the White House, U.S. Department of Education, and the National Science Foundation? All of these institutions have expressed interest in harnessing enthusiasm about these topics. See a recent Dear Colleague Letter from the Department of Education to that effect.

    • Mobile Learning Devices

    • Citizen Science

    • Crowdsourcing

    • Internet of Things

 

WHO WILL ANSWER THESE QUESTIONS?

Answering these questions will require a team of teachers, students, adminstrators, universities, private-public partnerships, professional societies, educational researchers, and developers. We are actively seeking educational researchers and developers interested in answering these questions.

 

Please feel free to comment, or reach out to us directly at vieyrasoft@gmail.com

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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