scholarly journals Treating Rapid Responses as Incorrect for Non-Timed Formative Tests

2019 ◽  
Vol 1 (1) ◽  
pp. 56-72
Author(s):  
Daniel B. Wright
Keyword(s):  
High Schools ◽  
Personalized Learning ◽  
Learning Systems ◽  
Formative Assessments ◽  
High Stakes ◽  
Ability Estimates ◽  
Rapid Responses ◽  
Response Alternatives ◽  
Time Required ◽  
Made In

AbstractWhen students respond rapidly to an item during an assessment, it suggests that they may have guessed. Guessing adds error to ability estimates. Treating rapid responses as incorrect answers increases the accuracy of ability estimates for timed high-stakes summative tests like the ACT. There are fewer reasons to guess rapidly in non-timed formative tests, like those used as part of many personalized learning systems. Data from approximately 75 thousand formative assessments, from 777 students at two northern California charter high schools, were analyzed. The accuracy of ability estimates is only slightly improved by treating responses made in less than five seconds as incorrect responses. Simulations show that the advantage is related to: whether guesses are made rapidly, the amount of time required for thoughtful responses, the number of response alternatives, and the preponderance of guessing. An R function is presented to implement this procedure. Consequences of using this procedure are discussed.

Robot Teaching, Pedagogy, and Policy

2020 ◽  
pp. 787-803
Author(s):  
Elana Zeide
Keyword(s):  
Artificial Intelligence ◽  
Analytical Methods ◽  
Personalized Learning ◽  
Educational Process ◽  
Learning Systems ◽  
Policy Decisions ◽  
Public Discussion ◽  
Teaching Pedagogy ◽  
Do So

This chapter looks at the use of artificial intelligence (AI) in education, which immediately conjures the fantasy of robot teachers, as well as fears that robot teachers will replace their human counterparts. However, AI tools impact much more than instructional choices. Personalized learning systems take on a whole host of other educational roles as well, fundamentally reconfiguring education in the process. They not only perform the functions of robot teachers but also make pedagogical and policy decisions typically left to teachers and policymakers. Their design, affordances, analytical methods, and visualization dashboards construct a technological, computational, and statistical infrastructure that literally codifies what students learn, how they are assessed, and what standards they must meet. However, school procurement and implementation of these systems are rarely part of public discussion. If they are to remain relevant to the educational process itself, as opposed to just its packaging and context, schools and their stakeholders must be more proactive in demanding information from technology providers and setting internal protocols to ensure effective and consistent implementation. Those who choose to outsource instructional functions should do so with sufficient transparency mechanisms in place to ensure professional oversight guided by well-informed debate.

scholarly journals A Rasch Model and Rating System for Continuous Responses Collected in Large-Scale Learning Systems

2020 ◽  
Vol 11 ◽  
Author(s):  
Benjamin Deonovic ◽  
Maria Bolsinova ◽  
Timo Bechger ◽  
Gunter Maris
Keyword(s):  
Rasch Model ◽  
Large Scale ◽  
Learning Systems ◽  
Rating System ◽  
Continuous Variables ◽  
High Stakes ◽  
Continuous Responses ◽  
Anytime Learning ◽  
Cold Start Problem ◽  
Over Time

An extension to a rating system for tracking the evolution of parameters over time using continuous variables is introduced. The proposed rating system assumes a distribution for the continuous responses, which is agnostic to the origin of the continuous scores and thus can be used for applications as varied as continuous scores obtained from language testing to scores derived from accuracy and response time from elementary arithmetic learning systems. Large-scale, high-stakes, online, anywhere anytime learning and testing inherently comes with a number of unique problems that require new psychometric solutions. These include (1) the cold start problem, (2) problem of change, and (3) the problem of personalization and adaptation. We outline how our proposed method addresses each of these problems. Three simulations are carried out to demonstrate the utility of the proposed rating system.

A Comparison of In-Vivo and Videoconference Momentary Time Sampling Observations of On-Task Behavior

2018 ◽  
Vol 45 (1) ◽  
pp. 3-13 ◽  
Author(s):  
Aaron J. Fischer ◽  
Evan H. Dart ◽  
Erica Lehman ◽  
Ben Polakoff ◽  
Sarah J. Wright
Keyword(s):  
Service Providers ◽  
Student Response ◽  
High Stakes ◽  
Reliability Indices ◽  
Momentary Time Sampling ◽  
School Based ◽  
Task Behavior ◽  
On Task Behavior ◽  
Time Required

Systematic direct observation (SDO) is frequently used in schools to document student response to evidence-based interventions, determine eligibility for special education services, and provide objective data during high-stakes decisions. However, there are several limitations associated with this widely used data collection tool including a shortage of service providers available to implement it and the significant travel time required for itinerant personnel. Using videoconferencing (VC) software to aid in the implementation of SDO is an intuitive application of technology that stands to increase the feasibility and efficiency with which SDO can be utilized in research and practice. The purpose of this study was to evaluate the reliability and equivalence of the results generated from two modes of SDO, traditional in-vivo SDO and SDO conducted through VC software. The results suggest that VC SDO produces estimates of student on-task behavior that are practically equivalent (i.e., ±3%) to estimates generated through traditional SDO. Furthermore, two frequently used reliability indices indicate that VC SDO results are adequately reliable against traditional in-vivo SDO. Implications for school-based practice are discussed.

XIII. A third catalogue of the comparative brightness of the stars; with an introductory account of an index to Mr. Flamsteed's observations of the fixed stars contained in the second volume of the Historia Cœlestis. To which are added, several useful results derived from that index

1797 ◽  
Vol 87 ◽  
pp. 293-324
Keyword(s):  
Zenith Distance ◽  
Arduous Task ◽  
General Catalogue ◽  
Time Required ◽  
Made In

In my earliest reviews of the heavens, I was much surprised to find many of the stars of the British catalogue missing. Taking it for granted that this catalogue was faultless, I supposed them to be lost. The deviation of many stars from the magnitude assigned to them in that catalogue, for the same reason, I looked upon as changes in the lustre of the stars. Soon after, however, I perceived that these conclusions had been premature, and wished it were possible to find some method that might serve to direct us from the stars in the British catalogue, to the original observations which have served as a foundation to it. The labour and time required for making a proper index, withheld me continually from undertaking the construction of it: but when I began to put the method of comparative brightness in practice, with a view to form a general catalogue, I found the indispensable necessity of having this index recur so forcibly, that I recommended it to my Sister to undertake the arduous task. At my request, and according to a plan which I laid down, she began the work about twenty months ago, and has lately finished it. The index has been made in the following manner. Every observation upon the fixed stars contained in the second volume of the Historia Cælestis was examined first, by casting up again all the numbers of the screws, in order to detect any error that might have been committed in reading off the zenith-distance by diagonal lines. The result of the computation being then corrected by the quantity given at the head of the column, and refraction being allowed for, was next compared with the column of the correct zenith-distance as a check.

Assessing Student Understanding

2017 ◽  
Vol 22 (6) ◽  
pp. 324
Author(s):  
Anthony Fernandes ◽  
Natasha Murray ◽  
Terrence Wyberg
Keyword(s):  
Large Scale ◽  
High Stakes Testing ◽  
Student Understanding ◽  
Formative Assessments ◽  
High Stakes ◽  
Testing Environment ◽  
School Year ◽  
Summative Assessments ◽  
Teachers And Students ◽  
Improve Student Learning

In the current high–stakes testing environment, a mention of assessment is inevitably associated with large–scale summative assessments at the end of the school year. Although these assessments serve an important purpose, assessing students' learning is an ongoing process that takes place in the classroom on a regular basis. Effectively gathering information about student understanding is integral to all aspects of mathematics instruction. Formative assessments conducted in the classroom have the potential to provide important feedback about students' understanding, guide future instruction to improve student learning, and provide roadmaps for both teachers and students in the process of learning.

scholarly journals The Effectiveness of a Systematic Algorithm for the Management of Vascular Injuries during the Laparoscopic Surgery

2015 ◽  
Vol 9 (3) ◽  
pp. 138-142 ◽  
Author(s):  
Carlo C. Passerotti ◽  
José A. Cruz ◽  
Sabrina T. Reis ◽  
Marcelo T. Okano ◽  
Ricardo J. Duarte ◽  
...  
Keyword(s):  
Laparoscopic Surgery ◽  
Vascular Injury ◽  
Vascular Injuries ◽  
Laparoscopic Complications ◽  
Before And After ◽  
Life Threatening ◽  
Potential Risks ◽  
Time Required ◽  
Training Protocol ◽  
Made In

Objectives: Currently, there is no standardized training protocol to teach surgeons how to deal with vascular injuries during laparoscopic procedures. The purpose of this study is to develop and evaluate the effectiveness of a standardized algorithm for managing vascular injury during laparoscopic nephrectomies. Materials and Methods: The performance of 6 surgeons was assessed during 10 laparoscopic nephrectomies in a porcine model. During the first and tenth operations, an injury was made in the renal vein without warning the surgeon. After the first procedure, the surgeons were instructed on how to proceed in dealing with the vascular injury, according to an algorithm developed by the designers of this study. The performance of each surgeon before and after learning the algorithm was assessed. Results: After learning the algorithm there was a decreased blood loss from 327 ± 403.11 ml to 37 ± 18.92 ml (p = 0.031) and decreased operative time from 43 ± 14.53 min to 27 ± 8.27 min (p = 0.015). There was also improvement in the time to start lesion repair from 147 ± 117.65 sec to 51 ± 39.09 sec (p = 0.025). There was a trend toward improvement in the reaction time to the injury (22 ± 21.55 sec vs. 14 ± 6.39, p = 0.188), the time required to control the bleeding (50 ± 94.2 sec vs. 14 ± 6.95 sec, p = 0.141), and the total time required to completely repair of the vascular injury (178 ± 170.4 sec vs. 119 ± 183.87 sec, p = 0.302). Conclusion: A standardized algorithm may help to reduce the potential risks associated with laparoscopic surgery. Further studies will help to refine and determine the benefits of standardized protocols such as that developed in this study for the management of life-threatening laparoscopic complications.

scholarly journals Multi-Agent Adaptive e-Learning System Based on Learning Styles

2021 ◽  
Vol 4 (1) ◽  
pp. 1-12
Author(s):  
Faith Ngami Kivuva ◽  
Elizaphan Maina ◽  
Rhoda Gitonga
Keyword(s):  
Learning Styles ◽  
Learning Process ◽  
Intelligent Agents ◽  
Personalized Learning ◽  
Learning Systems ◽  
Learning System ◽  
Personalized Recommendation ◽  
Information Agent ◽  
E Learning ◽  
Multi Agent

Most traditional e-learning system fails to provide the intelligence that a learner may require during their learning process. Different learners have different learning styles but the current e-learning systems are not able to provide personalized learning. In this paper, we discuss how intelligent agents can aid learners in their learning process. Three agents have been developed namely, learner agent, information agent, and tutor agents that will be integrated into a learning management system (Moodle). Learners are provided with a personalized recommendation based on the learning styles.

scholarly journals The Case for Integrating Multi-Source Data for a Fairer and Holistic Judgement of Competence in Medical Education & Training

2020 ◽  
Vol 14 (1) ◽  
pp. 1-9
Author(s):  
Subodh Dave ◽  
Roshelle Ramkisson ◽  
Chelliah R Selvasekar ◽  
Indranil Chakravorty
Keyword(s):  
Clinical Practice ◽  
Digital Literacy ◽  
Training Programme ◽  
Teaching Quality ◽  
Formative Assessments ◽  
Large Magnitude ◽  
High Stakes ◽  
Diverse Range ◽  
Academic Scholarship ◽  
High Level

Being a doctor in the 21st Century requires a diverse range of skills, a broad base of knowledge and a suite of professional values and attitudes that enable the clinical practice to be safe, effective and caring. Doctors, irrespective of their speciality, need to be knowledgeable and skilful not just in their area of expertise but also need a range of generic skills and capabilities such as communication, leadership, academic scholarship and research, teaching, quality improvement, advocacy, digital literacy to name a few. These capabilities, all relevant to clinical practice, are assessed routinely in clinical settings. This rich information about trainees, available from their formative assessments, does not inform high-stakes judgements about progression. Instead, these judgements are usually made on the basis of summative examinations conducted in simulated settings.   Unfortunately, these summative assessments have consistently delivered results with a large magnitude of the differential between the outcomes of candidates, based on factors such as ethnicity, gender, other protected characteristics and also the country of primary medical qualification. Formative assessment during training, however, is individualised and tends not to show this level of difference; leading to a situation where failure in summative examinations comes as a surprise to both trainees and to training programme directors.   There is evidence that periodic assessment of trainees’ acquisition of core capabilities can help make balanced, informed judgements about readiness for progression. The move from a pass/fail categorisation to a yet/not yet categorisation when coupled with appropriate remedial measures can improve, both the validity, as well as the fairness of assessments.     The large magnitude of the differential in outcomes of high-stakes assessments cannot be fixed by tweaking current assessment systems. Instead, there needs to be a recognition that high-level of capabilities consistently demonstrated in the workplace need to play a role in judgements about progression. Failure to do so is unfair, wasteful of public finances, and in breach of the trust places by the public, in training safe and competent clinicians.

scholarly journals Design of an Adaptive e-Learning System based on Multi-Agent Approach and Reinforcement Learning

2021 ◽  
Vol 11 (1) ◽  
pp. 6637-6644
Author(s):  
H. El Fazazi ◽  
M. Elgarej ◽  
M. Qbadou ◽  
K. Mansouri
Keyword(s):  
Reinforcement Learning ◽  
Learning Style ◽  
Learning Process ◽  
Learning Experience ◽  
Personalized Learning ◽  
Learning Objects ◽  
Learning Systems ◽  
Learning System ◽  
E Learning ◽  
Multi Agent

Adaptive e-learning systems are created to facilitate the learning process. These systems are able to suggest the student the most suitable pedagogical strategy and to extract the information and characteristics of the learners. A multi-agent system is a collection of organized and independent agents that communicate with each other to resolve a problem or complete a well-defined objective. These agents are always in communication and they can be homogeneous or heterogeneous and may or may not have common objectives. The application of the multi-agent approach in adaptive e-learning systems can enhance the learning process quality by customizing the contents to students’ needs. The agents in these systems collaborate to provide a personalized learning experience. In this paper, a design of an adaptative e-learning system based on a multi-agent approach and reinforcement learning is presented. The main objective of this system is the recommendation to the students of a learning path that meets their characteristics and preferences using the Q-learning algorithm. The proposed system is focused on three principal characteristics, the learning style according to the Felder-Silverman learning style model, the knowledge level, and the student's possible disabilities. Three types of disabilities were taken into account, namely hearing impairments, visual impairments, and dyslexia. The system will be able to provide the students with a sequence of learning objects that matches their profiles for a personalized learning experience.

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