scholarly journals Intellectual need for mathematical knowledge

2019 ◽  
Vol 60 ◽  
pp. 15-20
Author(s):  
Vytautas Miežys

Harel’s [2] notion of intel lectual need is refined by employing Davis’ [1] findingsabout interesting propositions in social sciences. A few hypothetical examples of how thisrevised definition might aid in planning mathematics lessons which provide meaningfulnessfor the students are presented.  

2019 ◽  
Vol 70 ◽  
pp. 06002
Author(s):  
Ekaterina Denisova ◽  
Anna Kruchkova ◽  
Natalia Klimova ◽  
Eugene Borokhovski

The article presents the results of studying the psychological characteristics of students in connection with their digital behavior. Authors assume that digital behavior of students can be associated with the features of their self-awareness, self-appraisal and value-semantic sphere. In addition, the importance of individual components in the hierarchy of educational values is studied in connection with personality characteristics. The study involved 102 people - students specializing in the social sciences and humanities. As a result, the authors found that students’ digital behavior in terms of the online presence is associated with their self-awareness, self-appraisal and value-semantic sphere. Students who spend online less than three hours a day will be more active, extroverted and confident in their real life (offline) than those who spend more time online. The importance of individual components in the hierarchy of educational values is associated with the features of self-awareness, self-attitude. Self-appraisal, self-confidence, sense of independence and high appreciation of one’s individuality are associated with a greater intellectual need, a more active and conscious desire to improve their own competence.


2017 ◽  
Vol 4 (3) ◽  
Author(s):  
Gabriella Bodnár ◽  
Dávid Bakonyvári ◽  
Brigitta Szilágyi

A Műegyetemre felvételt nyert hallgatók matematikai képességei, előismeretei igen eltérőek, sokan közülük komoly hiányosságokkal küzdenek. A bekerüléshez szükséges pontok megszerzéséért folytatott küzdelemben a megfelelő matematikai ismeretek elsajátítására már nem marad elegendő idő, energia. A diák a felvételi pontban kedvezőbb utakat járja be, ami a bekerülést követően fejti ki hatását. A középiskolában megszerezett tudást tekintve vegyes összetételű csoportok, ezen belül is a hiányzó alapok, jelentősen megnehezítik az egyetemi matematikaoktatást, számos problémát felvetve mind hallgatói, mind oktatói oldalról. Ily módon a hátrányokkal induló elsőéves esetét tekintve egy effajta lemaradás többet jelenthet az adott tantárgy nehezebb teljesítésénél, amin azt értjük, hogy adott ismeretanyag elsajátításához arányaiban több idő szükséges, mint a tantárgy ajánlott bemeneti szintjét jelentő tudással rendelkező évfolyamtársának. A helyzetet súlyosbítja, hogy a felsőoktatás jelenlegi keretei között kevésbé van mód differenciált oktatásra. Ezek a problémák a BME valamennyi karát érintik, így a Gazdaság- és Társadalomtudományi Karon folytatott képzésekre is kihatnak. 2016 augusztusában egy kéthetes szintrehozó tanfolyam keretén belül arra tettünk kísérletet, hogy a középiskolai anyag rendszerezésével, a tanultak átismétlésével segítsük az új hallgatók egyetemi tanulmányainak megkezdését. ***The mathematical capacities and previous knowledge of the students accepted at the Budapest University of Technology (BME) are very diverse; many of them face serious deficiencies. The fight for the points they are to collect in order to be accepted does not allow them to pay enough time and energy to acquire the adequate mathematical knowledge. The students choose the way more favourable for them in terms of the admission points, the effects of which will appear after they have been accepted.  The groups that are mixed concerning the knowledge gained at secondary school as well as the missing grounds considerably make teaching mathematics more difficult at the universities, and raise several problems on both the students’ and the teachers’ side. Thus, in case a first-grade student faces this type of disadvantage, lagging behind means more than just a more difficult acquisition of the certain material; he/she will need proportionally more time to learn the certain subject than his/her peers being in possession of the knowledge equal to the suggested entrance level of the subject. This situation is further rendered by the fact that within the frames of today’s higher education there are very limited possibilities of differentiated instruction. Each of the departments of the BME is concerned by this problem, likewise the courses conducted at the Department for Economic and Social Sciences. In August 2016, within the frames of a two-week bridging-the-gap course we made a try to help the new students start their university studies by repeating the adequate topics. 


Methodology ◽  
2019 ◽  
Vol 15 (1) ◽  
pp. 19-30 ◽  
Author(s):  
Knut Petzold ◽  
Tobias Wolbring

Abstract. Factorial survey experiments are increasingly used in the social sciences to investigate behavioral intentions. The measurement of self-reported behavioral intentions with factorial survey experiments frequently assumes that the determinants of intended behavior affect actual behavior in a similar way. We critically investigate this fundamental assumption using the misdirected email technique. Student participants of a survey were randomly assigned to a field experiment or a survey experiment. The email informs the recipient about the reception of a scholarship with varying stakes (full-time vs. book) and recipient’s names (German vs. Arabic). In the survey experiment, respondents saw an image of the same email. This validation design ensured a high level of correspondence between units, settings, and treatments across both studies. Results reveal that while the frequencies of self-reported intentions and actual behavior deviate, treatments show similar relative effects. Hence, although further research on this topic is needed, this study suggests that determinants of behavior might be inferred from behavioral intentions measured with survey experiments.


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