Thoughts on the Research of the Multi-evaluation System of the Quality of “Ideological and Political Theories Teaching in All Courses” in Colleges and Universities

The teaching quality evaluation system of "Ideological and Political Theories Teaching in All Courses" is far from perfect, as the appraisal content is unitary, and the appraisal method become too rigid. The evaluation system of teaching quality is quite an important mechanism and "baton" to promote the teaching quality of " Ideological and Political Theories Teaching in All Courses ". It has important and realistic research significance to construct a diversified teaching quality evaluation system of " Ideological and Political Theories Teaching in All Courses ". This article focuses on the teaching quality of appraisal content, evaluation subject, appraisal method, and believes that the overall framework of the multi-evaluation system of " Ideological and Political Theories Teaching in All Courses " teaching quality includes multi-evaluation index content, evaluation subject and multi-evaluation methods.

Combining K-Means Clustering and Random Forest to Evaluate the Gas Content of Coalbed Bed Methane Reservoirs

The accurate calculation of the gas content of coalbed bed methane (CBM) reservoirs is of great significance. However, due to the weak correlation between the logging response of coalbed methane reservoirs and the gas content parameters and strong nonlinear characteristics, it is difficult for conventional gas content calculation algorithms to obtain more reliable results. This paper proposes a CBM reservoir gas content assessment method combining K-means clustering and random forest. The K-means clustering is used to divide the reservoirs and distinguish the types to establish a random forest model. Judging from the evaluation effect of the research block, the prediction accuracy of the new method is significantly higher than that of the original method, and more accurate gas content prediction values can be obtained for different types of reservoirs. Studies have shown that this method can help the gas content evaluation of CBM reservoirs, improve the accuracy of gas content evaluation, and better support the exploration and development of CBM reservoirs. The results of this study show that the random forest method based on clustering can effectively distinguish the relationship between different logging responses and gas content. On this basis, the random forest algorithm modeling can effectively characterize the complex relationship between gas content and logging curve response. In the case of poor correlation between gas content and logging curve, the gas content of the reservoir can also be accurately calculated.

PROFIL KEMAMPUAN LITERASI DIGITAL KELAS X, XI DAN XII PADA MATA PELAJARAN BIOLOGI DI TASIKMALAYA

Penelitian ini bertujuan untuk melihat profil kemampuan literaai digital siswa kelas X, XI dan XII pada mata pelajaran Biologi di Tasikmalaya. Penelitian ini menggunakan pendekatan kuantitatif dengan format penelitian deskriptif. Populasi penelitian ini adalah seluruh siswa siswi kelas X, XI dan XII di Tasikmalaya tahun pelajaran 2019/2020 dengan jumlah sampel yang terkumpul sebanyak 121 yang terdiri dari 34 siswa kelas X, 52 siswa kelas XI dan 35 siswa kelas XII. Samping menggunakan Teknik stratified random sampling, yakni yang menjadi sampel adalah siswa kelas X , XI dan siswa kelas XII. Teknik pengumpulan data dalam penelitian ini dilakukan melalui kuesioner, observasi dan wawancara. Hasil temuan data disajikan kedalam 4 aspek sesuai dengan kuesioner yang telah disebarkan kepada para responden. Adapun empat aspek tersebut antara lain : pencarian di internet (internet searching), pandu arah hypertext (hypertextual navigation), evaluasi konten informasi (content evaluation), serta penyusunan pengetahuan (knowledge assembly). Oleh karena itu untuk kemampuan literasi digital di kelas X, XI dan XII pada mata pelajaran Biologi sudah tergolong tinggi dengan total skor rata-rata sebesar 5,40. Kata kunci : Kemampuan Literasi Digital, Deskriptif kuantitatif, Biologi

(Mis)perception of bias in print media: How depth of content evaluation affects the perception of hostile bias in an objective news report

The hostile media effect describes the tendency for partisans to evaluate media content as relatively biased against their positions. The present study investigates what specific contextual elements of a news report contribute to this effect and how it may be mitigated by the depth of content evaluation. A online study of 102 participants revealed that less bias is perceived in a newspaper article when evaluating specific aspects of the article with the text available for reference than when evaluating the overall bias without referring to the text. Moreover, being asked to consider overall article bias increased subsequent ratings of bias in the discrete elements of the text. These results suggest that the perception of media bias may be counteracted by encouraging deep, evidence-based considerations of where the alleged bias might lie, but only if this happens before the reader has the chance to form an opinion based on a cursory assessment.