scholarly journals Model Based Approach to Verification of Higher-Order Programs

2016 ◽  
Vol 216 ◽  
pp. 4-4
Author(s):  
Igor Walukiewicz
Keyword(s):  
2013 ◽  
Vol 8 (3) ◽  
Author(s):  
Fan Pan ◽  
Ying Hou ◽  
Zheng Hong ◽  
Lifa Wu ◽  
Haiguang Lai

2018 ◽  
Author(s):  
Marika C. Inhoff ◽  
Laura A. Libby ◽  
Takao Noguchi ◽  
Bradley C. Love ◽  
Charan Ranganath

AbstractThe development and application of concepts is a critical component of cognition. Although concepts can be formed on the basis of simple perceptual or semantic features, conceptual representations can also capitalize on similarities across feature relationships. By representing these types of higher-order relationships, concepts can simplify the learning problem and facilitate decisions. Despite this, little is known about the neural mechanisms that support the construction and deployment of these kinds of higher-order concepts during learning. To address this question, we combined a carefully designed associative learning task with computational model-based functional magnetic resonance imaging (fMRI). Participants were scanned as they learned and made decisions about sixteen pairs of cues and associated outcomes. Associations were structured such that individual cues shared feature relationships, operationalized as shared patterns of cue pair-outcome associations. In order to capture the large number of possible conceptual representational structures that participants might employ and to evaluate how conceptual representations are used during learning, we leveraged a well-specified Bayesian computational model of category learning [1]. Behavioral and model-based results revealed that participants who displayed a tendency to link experiences in memory benefitted from faster learning rates, suggesting that the use of the conceptual structure in the task facilitated decisions about cue pair-outcome associations. Model-based fMRI analyses revealed that trial-by-trial integration of cue information into higher-order conceptual representations was supported by an anterior temporal (AT) network of regions previously implicated in representing complex conjunctions of features and meaning-based information.


Author(s):  
Koen Van Leemput ◽  
Jesper D. Nielsen ◽  
Christian Bauer ◽  
Hartwig Siebner ◽  
Kristoffer H. Madsen ◽  
...  

2020 ◽  
Vol 11 (1) ◽  
pp. 39-47
Author(s):  
Diyas Age Larasati

ABSTRAKPembelajaran IPS SD menjadi pembelajaran yang membosankan, karena guru belum menerapkan model, metode, strategi pembelajaran yang inovatif. Guru juga hanya melatih siswa untuk hafalan-hafalan konsep IPS, belum melatih berpikir kritis. Discovery learning sebagai salah satu model pembelajaran memiliki keunggulan mengaktifkan siswa. Tahapan-tahapan model discovery learning mendukung siswa untuk berpikir kritis. Tujuan penelitian ini untuk mengetahui pengaruh model discovery learning berbasis higher order thinking skill terhadap kemampan berpikir kritis. Penelitian ini berjenis eksperimen semu, dengan rancangan Non Equivalent Control Group Design. Kelas eksperimen menerapkan model discovery learning berbasis Higher Order Thinking Skill, sedangkan kelas kontrol menerapkan model penugasan dan diskusi berbasis Higher Order Thinking Skill. Penelitian ini menggunakan populasi kelas V SDN Banyu Urip IX Surabaya. Dua kelas dipilih secara random sampling sebagai sampel penelitian. Kelas V-A berjumlah 32 siswa sebagai kelas eksperimen. Kelas V-B berjumlah 30 siswa sebagai kelas kontrol. Intrumen penelitian ini menggunakan soal (pretest dan posttest) dalam bentuk essai berjumlah 4 butir soal. Teknik pengumpulan data menggunakan penskoran terhadap hasil pretest dan posttest. Uji T digunakan untuk menguji hasil data penelitian. Hasil data penelitian menunjukkan rata-rata gainscore kelas eksperimen sebesar 5,75 lebih tinggi daripada kelas kontrol sebesar 2,6. Hasil data yang menggunakan uji-t. Hal ini dapat dilihat dari nilai t= 7,986 dan signifikansi dua ekor 0,000, sehingga p< 0,05. Hal tersebut membuktikan bahwa terdapat pengaruh model discovery learning berbasis higher order thinking skill terhadap kemampan berpikir kritis.Kata Kunci : Discovery Learning, Higher Order Thinking Skill, Berpikir kritisABSTRACTElementary school social studies learning becomes boring learning, because teachers have not applied innovative models, methods, and learning strategies. The teacher also only trains students to memorize social science concepts, not to train critical thinking. Discovery learning as one of the learning models has the advantage of activating students. The stages of the discovery learning model support students to think critically. The purpose of this study was to determine the effect of discovery learning models based on higher order thinking skills on critical thinking skills. This research is a quasi-experimental type, with a Non Equivalent Control Group Design. The experimental class applies the discovery learning model based on the Higher Order Thinking Skill, while the control class applies the assignment and discussion model based on the Higher Order Thinking Skill. This study uses a population of class V SDN Banyu Urip IX Surabaya. Two classes were chosen by random sampling as a research sample. Class V-A numbered 32 students as an experimental class. Class V-B totaling 30 students as a control class. The instruments of this study used 4 questions (pretest and posttest) in the form of essays. Data collection techniques used scoring of the results of the pretest and posttest. T test is used to test the results of research data. The results of the research data show that the average gaincore of the experimental class was 5.75 higher than the control class of 2.6. The results of data using the t-test. This can be seen from the value of t = 7.986 and the significance of two tails is 0.000, so that p <0.05. This proves that there is an influence of discovery learning model based on higher order thinking skills on critical thinking skills.Keywords: Discovery Learning, Higher Order Thinking Skill, Critical Thinking


2016 ◽  
Vol 304 ◽  
pp. 584-604 ◽  
Author(s):  
Tran Quoc Thai ◽  
Timon Rabczuk ◽  
Yuri Bazilevs ◽  
Günther Meschke

2017 ◽  
Vol 28 (9) ◽  
pp. 094004 ◽  
Author(s):  
Daniil Kazantsev ◽  
Enyu Guo ◽  
A B Phillion ◽  
Philip J Withers ◽  
Peter D Lee

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