Faculty and Staff

This paper presents a Bayesian framework for evaluative classification. Current education policy debates center on arguments about whether and how to use student test score data in school and personnel evaluation. Proponents of such use argue that refusing to use data violates both the public’s need to hold schools accountable when they use taxpayer dollars and students’ right to educational opportunities. Opponents of formulaic use of test-score data argue that most standardized test data is susceptible to fatal technical flaws, is a partial picture of student achievement, and leads to behavior that corrupts the measures.

A Bayesian perspective on summative ordinal classification is a possible framework for combining quantitative outcome data for students with the qualitative types of evaluation that critics of high-stakes testing advocate. This paper describes the key characteristics of a Bayesian perspective on classification, describes a method to translate a naïve Bayesian classifier into a point-based system for evaluation, and draws conclusions from the comparison on the construction of algorithmic (including point-based) systems that could capture the political and practical benefits of a Bayesian approach. The most important practical conclusion is that point-based systems with fixed components and weights cannot capture the dynamic and political benefits of a reciprocal relationship between professional judgment and quantitative student outcome data.

This is a brief text intended for use in undergraduate school-and-society classes. Your class may also be titled “Social foundations of education.” “Social foundations of education” is an interdisciplinary field that includes both humanities and social-science perspectives on schooling. It thus includes study of the philosophy and history of education as well as sociological, economic, anthropological, and political perspectives on schooling.

The core of most social foundations classes lies in the relationship between formal schooling and broader society. This emphasis means that while some parts of psychology may be related to the core issues of social foundations classes—primarily social psychology—the questions that are asked within a social-foundations class are different from the questions raised in child development, educational psychology, and most teaching-methods classes. For example, after finishing the first chapter of this text, you should be able to answer the question, “Why does the federal government pay public schools to feed poor students at breakfast and lunch?” Though there is some psychology research tying nutrition to behavior and learning, the policy is based on much broader expectations of schools. In this case, “Children learn better if they are well-fed” both is based on research and also is an incomplete answer.

The current debate over graduate rate calculations and results has glossed over the relationship between student migration and the accuracy of various graduation rates proposed over the past five years. Three general grade-based graduation rates have been proposed recently, and each has a parallel version that includes an adjustment for migration, whether international, internal to the U.S., or between different school sectors. All of the adjustment factors have a similar form, allowing simulation of estimates from real data, assuming different unmeasured net migration rates. In addition, a new age-based graduation rate, based on mathematical demography, allows the simulation of estimates on a parallel basis using data from Virginia's public schools.

Both the direct analysis and simulation demonstrate that graduation rates can only be useful with accurate information about student migration. A discussion of Florida's experiences with longitudinal cohort graduation rates highlights some of the difficulties with the current status of the oldest state databases and the need for both technical confidence and definitional clarity. Meeting the No Child Left Behind mandates for school-level graduation rates requires confirmation of transfers and an audit of any state system for accuracy, and basing graduation rates on age would be a significant improvement over rates calculated using grade-based data.

The spread of academic testing for accountability purposes in multiple countries has obscured at least two historical purposes of academic testing: community ritual and management of the social structure. Testing for accountability is very different from the purpose of academic challenges one can identify in community “examinations” in 19th century North America, or exams’ controlling access to the civil service in Imperial China. Rather than testing for ritual or access to mobility, the modern uses of testing are much closer to the state-building project of a tax census, such as the Domesday Book of medieval Britain after the Norman Invasion, the social engineering projects described in James Scott's Seeing like a State (1998), or the “mapping the world” project that David Nye described in America as Second Creation (2004). This paper will explore both the instrumental and cultural differences among testing as ritual, testing as mobility control, and testing as state-building.

One way to view ‘equitable pedagogy’ is through an opportunity to learn (OTL) lens, meaning that regardless of race, class, or culture, a student has access to rigorous and meaningful content, as well as appropriate resources and instruction necessary to learn and demonstrate understanding of that content. Assessment holds a unique position in the classroom in that it can both uncover whether inequitable conditions exist (i.e., performance gaps, denied OTL) and provide an OTL by mediating communication between teacher and students regarding learning progress and what is important to learn. Nevertheless, individuals entering teacher education programs often hold deficit views toward marginalized students, such as Language Minorities (LMs), believe that assessment strictly serves to evaluate learning, and do not do consider how language and culture influence student thinking–views supplanting assessment’s role at supporting an equitable pedagogy for LMs. Through surveys, interviews, program artifacts, and classroom observation, I report on a case study of one pre-service physics teacher, Dean, to depict how his expertise at assessing science did evolve throughout his yearlong teacher education program in terms of (a) becoming more knowledgeable of the role of language and (b) developing a belief in incorporating ‘discourse’ while assessing science. Within the case study, I analyze one particular episode from Dean’s teaching practicum to highlight remaining challenges for pre-service teachers to integrate science and language in classroom assessment—namely, interpreting students’ use of language along with their understanding of core science ideas. The findings underscore the need for connecting language and equity issues to content-area assessment in teacher preparation.

Myoelectric artificial limbs can significantly advance the state of the art in prosthetics, since they can be used to control mechatronic devices through muscular activity in a way that mimics how the subjects used to activate their muscles before limb loss. However, surveys indicate that dissatisfaction with the functionality of terminal devices underlies the widespread abandonment of prostheses. We believe that one key factor to improve acceptability of prosthetic devices is to attain human likeness of prosthesis movements, a goal which is being pursued by research on social and human–robot interactions. Therefore, to reduce early abandonment of terminal devices, we propose that controllers should be designed so as to ensure effective task accomplishment in a natural fashion. In this work, we have analyzed and compared the performance of three types of myoelectric controller algorithms based on surface electromyography to control an underactuated and multi-degrees of freedom prosthetic hand, the SoftHand Pro.

The goal of the present study was to identify the myoelectric algorithm that best mimics the native hand movements. As a preliminary step, we first quantified the repeatability of the SoftHand Pro finger movements and identified the electromyographic recording sites for able-bodied individuals with the highest signal-to-noise ratio from two pairs of muscles, i.e., flexor digitorum superficialis/extensor digitorum communis, and flexor carpi radialis/extensor carpi ulnaris. Able-bodied volunteers were then asked to execute reach-to-grasp movements, while electromyography signals were recorded from flexor digitorum superficialis/extensor digitorum communis as this was identified as the muscle pair characterized by high signal-to-noise ratio and intuitive control. Subsequently, we tested three myoelectric controllers that mapped electromyography signals to position of the SoftHand Pro. We found that a differential electromyography-to-position mapping ensured the highest coherence with hand movements. Our results represent a first step toward a more effective and intuitive control of myoelectric hand prostheses.

Introduction: Options currently available to individuals with upper limb loss range from prosthetic hands that can perform many movements, but require more cognitive effort to control, to simpler terminal devices with limited functional abilities. We attempted to address this issue by designing a myoelectric control system to modulate prosthetic hand posture and digit force distribution.

Methods: We recorded surface electromyographic (EMG) signals from five forearm muscles in eight able-bodied subjects while they modulated hand posture and the flexion force distribution of individual fingers. We used a support vector machine (SVM) and a random forest regression (RFR) to map EMG signal features to hand posture and individual digit forces, respectively. After training, subjects performed grasping tasks and hand gestures while a computer program computed and displayed online feedback of all digit forces, in which digits were flexed, and the magnitude of contact forces. We also used a commercially available prosthetic hand, the i-Limb (Touch Bionics), to provide a practical demonstration of the proposed approach’s ability to control hand posture and finger forces.

Results: Subjects could control hand pose and force distribution across the fingers during online testing. Decoding success rates ranged from 60% (index finger pointing) to 83–99% for 2-digit grasp and resting state, respectively. Subjects could also modulate finger force distribution.

Discussion: This work provides a proof of concept for the application of SVM and RFR for online control of hand posture and finger force distribution, respectively. Our approach has potential applications for enabling in-hand manipulation with a prosthetic hand.

The concept of postural synergies of the human hand has been shown to potentially reduce complexity in the neuromuscular control of grasping. By merging this concept with soft robotics approaches, a multi degrees of freedom soft-synergy prosthetic hand [SoftHand-Pro (SHP)] was created. The mechanical innovation of the SHP enables adaptive and robust functional grasps with simple and intuitive myoelectric control from only two surface electromyogram (sEMG) channels. However, the current myoelectric controller has very limited capability for fine control of grasp forces. We addressed this challenge by designing a hybrid-gain myoelectric controller that switches control gains based on the sensorimotor state of the SHP. This controller was tested against a conventional single-gain (SG) controller, as well as against native hand in able-bodied subjects. We used the following tasks to evaluate the performance of grasp force control: (1) pick and place objects with different size, weight, and fragility levels using power or precision grasp and (2) squeezing objects with different stiffness. Sensory feedback of the grasp forces was provided to the user through a non-invasive, mechanotactile haptic feedback device mounted on the upper arm. We demonstrated that the novel hybrid controller enabled superior task completion speed and fine force control over SG controller in object pick-and-place tasks. We also found that the performance of the hybrid controller qualitatively agrees with the performance of native human hands.