scholarly journals Intasc Standard Cores: Raising Students’ English Modality Competence

2016 ◽  
Vol 10 (2) ◽  
pp. 111
Author(s):  
Muliani Muliani

This research aimed at raising the students’ modality competence with the implementation of a teaching model which was called as Interstate New Teachers Assessment and Support Consortium (INTASC) model that covering ten standards. It was expected that this research could give numerous contribution in teaching English, particularly in teaching English Modality where the problem found was that the students got difficulty in using modal verbs regarding both tense and aspect in which consequently would affect the communicative competence of the students. In the form of Research and Development, this research was carried by means of implementing validated instrument and 10 modules in the small and large scale assessments that involving 50 students in the small scale assessment and 80 students in the large-scale assessment. Standard 1-2 dealt with the students’ need and diversity of learning while standard 3-7 dealt with various instructions teaching the content knowledge regarding the use of English modality. Furthermore, standard 8-10 dealt with summative assessment, reflection, and professional development. Eventually, it is found that the level of learning of the students raise supported by the data that 94% of the level of learning can be achieved by the students while it was only 6% of the modality expressions cannot be used properly. It can be noted that this teaching model can assist the students in achieving the modality competence by having a very well-sequenced procedures of teaching in which this teaching model starts from considering the prior knowledge, the need, and the students’ diversity before creating further instructions regarding the content knowledge where the modality competence is the main goal to achieve.

2018 ◽  
Vol 43 (7) ◽  
pp. 543-561 ◽  
Author(s):  
Yuan-Pei Chang ◽  
Chia-Yi Chiu ◽  
Rung-Ching Tsai

Cognitive diagnostic computerized adaptive testing (CD-CAT) has been suggested by researchers as a diagnostic tool for assessment and evaluation. Although model-based CD-CAT is relatively well researched in the context of large-scale assessment systems, this type of system has not received the same degree of research and development in small-scale settings, such as at the course-based level, where this system would be the most useful. The main obstacle is that the statistical estimation techniques that are successfully applied within the context of a large-scale assessment require large samples to guarantee reliable calibration of the item parameters and an accurate estimation of the examinees’ proficiency class membership. Such samples are simply not obtainable in course-based settings. Therefore, the nonparametric item selection (NPS) method that does not require any parameter calibration, and thus, can be used in small educational programs is proposed in the study. The proposed nonparametric CD-CAT uses the nonparametric classification (NPC) method to estimate an examinee’s attribute profile and based on the examinee’s item responses, the item that can best discriminate the estimated attribute profile and the other attribute profiles is then selected. The simulation results show that the NPS method outperformed the compared parametric CD-CAT algorithms and the differences were substantial when the calibration samples were small.


2013 ◽  
Author(s):  
Laura S. Hamilton ◽  
Stephen P. Klein ◽  
William Lorie

Land ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 295
Author(s):  
Yuan Gao ◽  
Anyu Zhang ◽  
Yaojie Yue ◽  
Jing’ai Wang ◽  
Peng Su

Suitable land is an important prerequisite for crop cultivation and, given the prospect of climate change, it is essential to assess such suitability to minimize crop production risks and to ensure food security. Although a variety of methods to assess the suitability are available, a comprehensive, objective, and large-scale screening of environmental variables that influence the results—and therefore their accuracy—of these methods has rarely been explored. An approach to the selection of such variables is proposed and the criteria established for large-scale assessment of land, based on big data, for its suitability to maize (Zea mays L.) cultivation as a case study. The predicted suitability matched the past distribution of maize with an overall accuracy of 79% and a Kappa coefficient of 0.72. The land suitability for maize is likely to decrease markedly at low latitudes and even at mid latitudes. The total area suitable for maize globally and in most major maize-producing countries will decrease, the decrease being particularly steep in those regions optimally suited for maize at present. Compared with earlier research, the method proposed in the present paper is simple yet objective, comprehensive, and reliable for large-scale assessment. The findings of the study highlight the necessity of adopting relevant strategies to cope with the adverse impacts of climate change.


2017 ◽  
Vol 55 (3) ◽  
pp. 1312-1326 ◽  
Author(s):  
Cecília G. Leal ◽  
Jos Barlow ◽  
Toby A. Gardner ◽  
Robert M. Hughes ◽  
Rafael P. Leitão ◽  
...  

2021 ◽  
Vol 150 (4) ◽  
pp. A80-A81
Author(s):  
Jakob Tougaard ◽  
Thomas Folegot ◽  
Christ de Jong ◽  
Emily T. Griffiths ◽  
Alexander M. von Benda-Beckmann ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document