Physics Education Research

Educational research projects include:

• Lab development and assessment. A recent project includes introductory physics labs using modern sensors (e.g. a Local Positioning System)
• Cross disciplinary and innovative biomedical physics summer course for life science majors and pre-health students

• Development of biomedical student activities. Some recent projects include: 

            •CT 
            •Pulse Oximetry 
            •Electric circuits and EKGs
            •Bioelectrical Impedance Analysis 
            •Planar imaging 

• Multimedia modules with pre-lecture videos by biomedical experts and authentic medically relevant course material. Our group builds on a successful network of medical and biomedical professionals
• Assessment of student engagement and attitude

We are developing and assessing innovative curriculum for introductory physics for the life science (IPLS) with a particular focus on pre-health students. Some guidelines that address the need for such a curriculum can be found for example in the IPLS Conference Report and the AAPT Recommendations for the Undergraduate Physics Laboratory Curriculum. We try to address some fundamental challenges and opportunities in undergraduate STEM education:

• The medical field has and continues to evolve rapidly and physics pre-health education has not kept up with these changes
• There is a lack of adequate research validated teaching materials aimed at pre-health and life science undergraduate physics courses
• Traditional teacher centered methods have shown to be ineffective
• New technology allows effective integration of multimedia content online and provides new assessment tools
• Active learning and flipped classroom instruction have shown to be successful by various studies

An important research component of our work is the assessment of the effectiveness and impact of the curriculum on students. This requires extensive formative and summative assessments to measure impacts on student learning and the effect of instruction on student attitude and engagement. This work has been supported by three grants of the National Science Foundation.

​Digital Sensors

​Digital sensors are ubiquitous in today's society and found in places ranging from the Hubble space telescope to cell phones.There are two main types of digital sensors: 
Charge-Coupled Devices (CCDs) and Complementary Metal–Oxide–Semiconductors (CMOS). 

Dr. Widenhorn studies the performance of these sensors with the goal to understand the characteristics better and improve image quality. We investigate the characteristics and performance of CMOS active pixel sensors and CCD imagers used in cell phones, regular consumer cameras, and scientific applications.  Past and current projects include:

• Computation of dark frames 
• Thermal noise in digital imagers 
• Impurity detection and localization in semiconductors 
• Meyer-Neldel rule 
• Spatial resolution and Point Spread Function of digital imagers
• Performance of medical image sensors 
• Noise characteristic of different read out circuits in CCDs 
• "Ghosting” in CCD imagers

Since the advent of digital cameras a source of noise due to heat, called dark current, has been a pernicious unwanted signal in images taken by astronomers, scientists, and photographers.  We study this noise, what causes it, its peculiarities, and maybe most importantly, how best to remove it.  Our publications include an algorithm that removes the dark current based upon the pixels with the greatest amounts of dark current.  These pixels, so called hot pixels, can essentially be used as thermometers to predict the amount of noise that should be removed from all the other pixels.  Additionally, we have reported on a particular type of pixel that actually produces different amounts of dark noise when illuminated with light than when the shutter is closed. These pixels produce dark current non-linearly with respect to exposure time, a complication as scientists and astronomers rely upon the linear signal to make accurate measurements.  We have produced a model that attempts to explain how this behavior can be explained by the presence of an impurity located in a very particular region of the pixel.