Surprise

About: Surprise is a research topic. Over the lifetime, 4371 publications have been published within this topic receiving 99386 citations.

Can We Get Better Assessment From A Tutoring System Compared to Traditional Paper Testing? Can We Have Our Cake (Better Assessment) and Eat It too (Student Learning During the Test)?

Abstract: Dynamic assessment (DA) has been advocated as an interactive approach to conducting assessments to students in the learning systems Sternberg and others proposed to give students tests to see how much assistance it takes a student to learn a topic; and to use as a measure of their learning gain To researchers in the ITS community, it comes as no surprise that measuring how much assistance a student needs to complete a task successfully is probably a good indicator of this lack of knowledge However, a cautionary note is that conducting DA takes more time than simply administering regular test items to students In this paper, we report a study analyzing 40-minutes data of totally 1,392 students from two school years The result suggests that for the purpose of assessing student performance, it is more efficient for students to take DA than just having practice items.

When are successes more surprising than failures

Abstract: Surprise has been described in various contexts as a neutral, a positive, or a negative emotion. Six experiments are reported in which surprise ratings of unexpected positive and negative outcomes, with identical prior probabilities, were compared. For unexpected occurrences of events that are beyond the control of the protagonist, successes were consistently perceived as more surprising than failures. For unexpected action controlled outcomes for which the protagonist was partly responsible, failures were rated as more surprising than successes. The findings are interpreted as being due to an implicit contrast between out-of-control situations and success, in the first case, and between goal-directed efforts and failure, in the second.

Converging Evidence for Emotional Structures: Theory and Method

Abstract: The task of the psychoanalytic researcher is in part to verify what the clinician already knows. For much of what the researcher finds the response of the clinician must be, “I knew that all along.” But the goal of research must also be to discover what we have previously had no access to, and what we seem to know, but wrongly. You can see that the work of the researcher is in some respects like that of the patient as well as the therapist. All participants in the psychoanalytic enterprise are attempting to detect psychic structures that have previously been unrecognized. At all levels, the achievement of new knowledge, the “surprise”, depends on the articulation of connections and associations so that gaps can be uncovered and ambiguities resolved.

Sentimental Analysis for Airline Twitter data

Abstract: Social Media has taken the world by surprise at a swift and commendable pace. With the advent of any kind of circumstances may it be related to social, political or current affairs the sentiments of people throughout the world are expressed through their help, making them suitable candidates for sentiment mining. Sentimental analysis becomes highly resourceful for any organization who wants to analyse and enhance their products and services. In the airline industries it is much easier to get feedback from astute data source such as Twitter, for conducting a sentiment analysis on their respective customers. The beneficial factors relating to twitter sentiment analysis cannot be impeded by the consumers who want to know the who's who and what's what in everyday life. In this paper we are classifying sentiment of Twitter messages by exhibiting results of a machine learning algorithm using R and Rapid Miner. The tweets are extracted and pre-processed and then categorizing them in neutral, negative and positive sentiments finally summarising the results as a whole. The Naive Bayes algorithm has been used for classifying the sentiments of recent tweets done on the different airlines.