Impact of Position and Orientation of RFID Tags on Real Time Asset Tracking in a Supply Chain

We studied the characteristics of four commercially available RFID tags such as their orientation on an asset and their position in a three dimensional real world environment to obtain comprehensive data to substantiate a baseline for the use of RFID technology in a diverse supply chain management setting. Using RFID tags manufactured by four different vendors and a GHz Transverse Electromagnetic (GTEM) cell, in which an approximately constant electromagnetic (EM) field was maintained, we characterized the tags based on horizontal and vertical orientation on a simulated asset. With these baseline characteristics determined, we moved two of the four tags through a real world environment in three dimensions using an industrial robotic system to determine the effect of asset position in relation to the reader on tag readability. Combining the data collected over these two studies, we provide a rich analysis of the feasibility of asset tracking in a real world supply chain, where there would likely be multiple tag types. We offer fine grained analyses of the tag types and make recommendations for diverse supply chain asset tracking

Mind wandering during learning with an intelligent tutoring system

Mind wandering (zoning out) can be detrimental to learning outcomes in a host of educational activities, from reading to watching video lectures, yet it has received little attention in the field of intelligent tutoring systems (ITS). In the current study, participants self-reported mind wandering during a learning session with Guru, a dialogue-based ITS for biology. On average, participants interacted with Guru for 22 minutes and reported an average of 11.5 instances of mind wandering, or one instance every two minutes. The frequency of mind wandering was compared across five different phases of Guru (Common-Ground-Building Instruction, Intermittent Summary, Concept Map, Scaffolded Dialogue, and Cloze task), each requiring different learning strategies. The rate of mind wandering per minute was highest during the Common-Ground-Building Instruction and Scaffolded Dialogue phases of Guru. Importantly, there was significant negative correlation between mind wandering and learning, highlighting the need to address this phenomena during learning with ITSs

An open vocabulary approach for estimating teacher use of authentic questions in classroom discourse

Automatic assessment of the quality of classroom discourse can have a transformative effect on research and practice on improving teaching effectiveness. We improve on a previous automated method to measure teacher authentic questions – open-ended questions without pre-scripted responses that predict student achievement growth – using classroom audio and expert question codes from two sources: (1) a large archival database of text transcripts of 428 class-sessions from 116 classrooms, and (2) a newly collected sample of 132 high-quality audio recordings with automatic speech recognition transcripts from 27 classrooms. Whereas previous work utilized a “closed vocabulary” approach, consisting of 732 pre-defined word, sentence, and discourse level features, the present “open vocabulary” approach exclusively utilized word and phrase counts from the transcripts themselves. The two approaches yielded substantial, but statistically equivalent, correlations with gold-standard human codes of authenticity (Pearson r’s of 0.396 vs. 0.424 and 0.602 vs. 0.613 for datasets 1 and 2, respectively). Importantly, averaging estimates from the two approaches resulted in statistically significant improvements over either approach (r’s of 0.492 and 0.686 for datasets 1 and 2, respectively). We discuss implications of our findings for automated analysis of classroom discourse

Tracking online reading of college students

We conducted a pilot study that used kernel-level packet capture to record the web pages visited by college students and the reading difficulty of those pages. Our results indicate that i) no students were fully compliant in their participation, ii) the number of texts encountered by participants was highly skewed, iii) the reading difficulty of texts was about 7th grade, M = 7.24, CI95[7.04,7.43], though difficulty varied by participant, and iv) the increasing use of encryption is likely a limiting factor for using kernel-level packet capture to measure online reading in the future

Assessing the dialogic properties of classroom discourse: Proportion models for imbalanced classes

Automatic assessment of dialogic properties of classroom discourse would benefit several widespread classroom observation protocols. However, in classrooms with low incidences of dialogic discourse, assessment can be highly biased against detecting dialogic properties. In this paper, we present an approach to addressing this imbalanced class problem. Rather than perform classifications at the utterance level, we aggregate feature vectors to classify proportions of dialogic properties at the class-session level and achieve a moderate correlation with actual proportions, r(130) = .50, p \u3c .001, CI95[.36,.61] . We show that this approach outperforms aggregating utterance level classifications, r(130) = .27, p = .001, CI95[.11,.43], is stable for both low and high dialogic classrooms, and is stable across both automatic speech recognition and human transcripts