scholarly journals A Computational Strategy for Classification of Enem Issues Based on Item Response Theory

2020 ◽  
Vol 27 (1) ◽  
pp. 92-111
Author(s):  
Gustavo Henrique Nunes ◽  
Bruno Alberto Soares Oliveira ◽  
Ciniro Aparecido Leite Nametala
Keyword(s):  
High School ◽  
Item Response Theory ◽  
Item Response ◽  
Generation System ◽  
Response Theory ◽  
Hit Rate ◽  
System A ◽  
Intelligent Simulation ◽  
Computational Strategy

The National High School Examination (ENEM) gains each year more importance, as it gradually, replacing traditional vestibular. Many simulations are done almost randomly by teachers or systems, with questions chosen without discretion. With this methodology, if a test needs to be reapplied, it is not possible to recreate it with questions that have the same difficulty as those used in the first evaluation. In this context, the present work presents the development of an ENEM Intelligent Simulation Generation System that calculates the parameters of Item Response Theory (TRI) of questions that have already been applied in ENEM and, based on them, classifies them. in groups of difficulty, thus enabling the generation of balanced tests. For this, the K-means algorithm was used to group the questions into three difficulty groups: easy, medium and difficult. To verify the functioning of the system, a simulation with 180 questions was generated along the ENEM model. It could be seen that in 37.7% of cases this happened. This hit rate was not greater because the algorithm confounded the difficulty of issues that are in close classes. However, the system has a hit rate of 92.8% in the classification of questions that are in distant groups.

scholarly journals Building a Self-Confidence Scale According to the Item Response Theory for High School Students in Jordan

2021 ◽  
Vol 15 (3) ◽  
pp. 17
Author(s):  
Hani Alkhaldi ◽  
Malek Alkhutaba ◽  
Mohammad Al-Dlalah
Keyword(s):  
High School ◽  
High School Students ◽  
Item Response Theory ◽  
Item Response ◽  
Experimental Sample ◽  
Response Theory ◽  
School Students ◽  
Male And Female ◽  
Final Version ◽  
Self Confidence

This study aimed to build self-confidence for high school students in Al-Mafraq Governorate in Jordan following the Item Response Theory (IRT). The scale included its initial version (50) items. To ensure the external validity of the scale, it was reviewed by several experts. According to the experts’ feedback, some items should be deleted or modified. The final version of the scale included (44) items. The scale was further applied to an experimental sample of (310) male and female students to verify psychometricians’ characteristics. Finally, the scale was administered to a sample of (1060) male and female high school students in Al-Mafraq Governorate. Data were collected, coded, and analyzed using statistical programs (SPSS and WINSTEPS). The most important results were the following: the self-confidence measure was one-dimensional, which means it measures only a single dimension. The results further revealed identical to the partial estimation model, and the index of average matching of individuals and the external and internal items approached zero, and the standard deviation approached the correct one. The estimated values of the distinct thresholds for the scale items showed a clear discriminatory ability and the emergence of particular threshold scores on the scale. After deleting the paragraphs that did not fit the study's model, the scale's final version included 39 items. The results also showed that the transfer values of logistical capacity units were within (-2.88 -2.77), within the IRT's accepted range.

PENGEMBANGAN DAN ANALISIS SOAL ULANGAN KENAIKAN KELAS KIMIA SMA KELAS X BERDASARKAN CLASSICAL TEST THEORY DAN ITEM RESPONSE THEORY

2011 ◽  
Vol 16 (2) ◽  
pp. 109
Author(s):  
Mr Nahadi ◽  
Mrs Wiwi Siswaningsih ◽  
Mr Ana Rofiati
Keyword(s):  
High School ◽  
Item Response Theory ◽  
Item Response ◽  
Classical Test Theory ◽  
First Grade ◽  
Test Theory ◽  
Final Examination ◽  
Response Theory ◽  
Test Items ◽  
Classical Test

This research is title “Test Development and Analysis of First Grade Senior High School Final Examination in chemistry Based on Classical Test Theory and Item Response Theory”. This research is conducted to develop a standard test instrument for final examination in senior high school at first grade using analysis based on classical test theory and item response theory. The test is a multiple choice test which consists of 75 items. Each item has five options. The research method is research and development method to get a product of test items which fulfill item criterion such as validity, reliability, item discrimination, item difficulty and distracting options quality based on classical test theory and validity, reliability, item discrimination, item difficulty and pseudo-guessing based on item response theory. The three parameter item response theory model is used in this research. Research and development method is conducted until preliminary field test to 102 first grade students in senior high school. Based on the research result, the test fulfills criterion as a good instrument based on classical test theory and item response theory. The final examination test items have vary of item quality so that some of them need a revision to make them better either for the stem and the options. From the total of 75 test items, 21 test items are declined and 54 test items are accepted.

scholarly journals Item Response Theory Modeling of High School Students’ Behavior in a High-Stakes Exam

OALib ◽  
2019 ◽  
Vol 06 (02) ◽  
pp. 1-22
Author(s):  
Helen Gomes ◽  
Raul Matsushita ◽  
Sergio Da Silva
Keyword(s):  
High School ◽  
High School Students ◽  
Item Response Theory ◽  
Item Response ◽  
Response Theory ◽  
School Students ◽  
High Stakes

scholarly journals Intelligent Topical Sentiment Analysis for the Classification of E-Learners and Their Topics of Interest

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
M. Ravichandran ◽  
G. Kulanthaivel ◽  
T. Chellatamilan
Keyword(s):  
Item Response Theory ◽  
Item Response ◽  
Real Life ◽  
Response Theory ◽  
Sentence Level ◽  
Traditional Classification ◽  
Massive Number ◽  
The Common ◽  
Document Level

Every day, huge numbers of instant tweets (messages) are published on Twitter as it is one of the massive social media for e-learners interactions. The options regarding various interesting topics to be studied are discussed among the learners and teachers through the capture of ideal sources in Twitter. The common sentiment behavior towards these topics is received through the massive number of instant messages about them. In this paper, rather than using the opinion polarity of each message relevant to the topic, authors focus on sentence level opinion classification upon using the unsupervised algorithm named bigram item response theory (BIRT). It differs from the traditional classification and document level classification algorithm. The investigation illustrated in this paper is of threefold which are listed as follows:(1)lexicon based sentiment polarity of tweet messages;(2)the bigram cooccurrence relationship using naïve Bayesian;(3)the bigram item response theory (BIRT) on various topics. It has been proposed that a model using item response theory is constructed for topical classification inference. The performance has been improved remarkably using this bigram item response theory when compared with other supervised algorithms. The experiment has been conducted on a real life dataset containing different set of tweets and topics.

Sign in / Sign up

Export Citation Format

Share Document