"978-80-558-0232-9" . . . "Osvojen\u00ED grafick\u00E9ho a statistick\u00E9ho zpracov\u00E1n\u00ED dat ze vzd\u00E1len\u00FDch re\u00E1ln\u00FDch experiment\u016F"@cs . . . . "S" . "The essential part of experimenting in physics is a correct statistical and graphical data processing, including the determination of a physical constant or a parameter from the fit. Moreover, graphs in physics serve for immediate evaluation of the reliability of a measurement and its errors and to decide whether the theory (model function) and experimental results correspond to each other. Graphs are a common way for the presentation of experimental results. We bring the opportunity for experimenting in those topics where an experiment is not usually performed (e.g. because of the lack of equipment, too complicated or dangerous experiment). Within the integrated e-learning strategy we assume students' performance of a remotely controlled experiment, which includes just observation and then the recording and downloading of experimental values. We put the emphasis on the subsequent processing of data, with the use of MS-Excel-like software. For example: concerning the photoelectric effect students have to fit 5 experimental points with a line (excluding the frequencies bellow the threshold) in order to verify the Einstein's formula and to determine the Planck constant and the work function. Concening radioactivity and common ways how to protect ourselves against ionizing radiation, students may reveal the importance of the number of measurements and the convergence of mean values to a certain curve that may be compared with the model function, considering the errorbars. The main advantage of a remote laboratory experiment on radioactivity is the acccess to a large statistical set of values measured in the non-stop automatized measurement mode. Moreover, the Poisson distribution may be compared with the data from the monitoring of the background. The integrated e-learning strategy is worth introducing the common scientific ways of processing of experimental data."@en . . "11320" . "Gaining graphical and statistical data processing from remotely controlled experiment"@en . . "Osvojen\u00ED grafick\u00E9ho a statistick\u00E9ho zpracov\u00E1n\u00ED dat ze vzd\u00E1len\u00FDch re\u00E1ln\u00FDch experiment\u016F"@cs . "radioactivity; photoelectric effect; statistical data processing; graphical data processing; remote experiments; integrated e-learning strategy"@en . . . . . "Zborn\u00EDk abstraktov a pr\u00EDspevkov z XVIII. medzin\u00E1rodnej konferencie" . "9"^^ . "Nitra" . . "Ra\u010Dkova dolina, Slovensko" . . . "94814" . "1"^^ . "D\u016Fle\u017Eitou sou\u010D\u00E1st\u00ED fyzik\u00E1ln\u00EDch experiment\u016F je spr\u00E1vn\u00E9 zpracov\u00E1n\u00ED s vyu\u017Eit\u00EDm statistiky a graf\u016F, a to v\u010Detn\u011B ur\u010Den\u00ED fyzik\u00E1ln\u00EDch konstant \u010Di materi\u00E1lov\u00FDch parametr\u016F z fitu. Nav\u00EDc grafy slou\u017E\u00ED k okam\u017Eit\u00E9mu posouzen\u00ED spolehlivosti a chyb m\u011B\u0159en\u00ED stejn\u011B jako k posouzen\u00ED, zda teorie (model) a experiment\u00E1ln\u00ED data jsou ve vz\u00E1jemn\u00E9m souladu. Graf je z\u00E1kladn\u00ED prost\u0159edek k prezentaci nam\u011B\u0159en\u00FDch hodnot a v\u00FDsledk\u016F. V p\u0159\u00EDsp\u011Bvku p\u0159edstavujeme mo\u017Enosti experimentovat ve vybran\u00FDch t\u00E9matech, kde se pokusy b\u011B\u017En\u00E9 neprov\u00E1d\u00ED (nap\u0159. proto\u017Ee na \u0161kol\u00E1ch chyb\u00ED pom\u016Fcky nebo pokus je p\u0159\u00EDli\u0161 slo\u017Eit\u00FD \u010Di nebezpe\u010Dn\u00FD). V r\u00E1mci strategie v\u00FDuky zvan\u00E9 integrovan\u00FD e-learning p\u0159edpokl\u00E1d\u00E1me, \u017Ee studenti provedou vzd\u00E1len\u00E9 m\u011B\u0159en\u00ED v\u010Detn\u011B c\u00EDlen\u00E9ho z\u00E1znamu a sta\u017Een\u00ED vlastn\u00EDch experiment\u00E1ln\u00EDch dat. D\u016Fraz je v\u0161ak kladen na n\u00E1sledn\u00E9 zpracov\u00E1n\u00ED nam\u011B\u0159en\u00FDch hodnot, nap\u0159. s pou\u017Eit\u00EDm softwaru typu MS Excel. Nap\u0159.: p\u0159i studiu vn\u011Bj\u0161\u00EDho fotoefektu studenti mus\u00ED prolo\u017Eit 5 experiment\u00E1ln\u00EDch bod\u016F p\u0159\u00EDmkou (mimo podprahov\u00E9 frekvence) s c\u00EDlem ov\u011B\u0159it Einsteinovu rovnici pro fotoefekt a vyhodnotit Planckovu konstantu a v\u00FDstupn\u00ED pr\u00E1ci. P\u0159i studiu radioaktivity a z\u00E1kladn\u00EDch zp\u016Fsob\u016F ochrany p\u0159ed ionizuj\u00EDc\u00EDm z\u00E1\u0159en\u00EDm studenti mohou pochopit v\u00FDznam po\u010Dtu opakov\u00E1n\u00ED m\u011B\u0159en\u00ED pro statistick\u00E9 zpracov\u00E1n\u00ED a konvergenci pr\u016Fm\u011Br\u016F k hladk\u00E9 k\u0159ivce, kter\u00E1 m\u016F\u017Ee b\u00FDt porovn\u00E1na s modelovou funkc\u00ED s ohledem na chyby m\u011B\u0159en\u00ED. Hlavn\u00ED v\u00FDhoda vzd\u00E1len\u00FDch experiment\u016F ke studiu radioaktivity je p\u0159\u00EDstup k rozs\u00E1hl\u00E9mu souboru experiment\u00E1ln\u00EDch hodnot, kter\u00E9 byly nam\u011B\u0159eny v nep\u0159etr\u017Eit\u00E9m automatick\u00E9m re\u017Eimu. Speci\u00E1ln\u011B lze vyu\u017E\u00EDt hodnoty p\u0159\u00EDrodn\u00EDho radioaktivn\u00EDho pozad\u00ED k ov\u011B\u0159en\u00ED Poissonova rozd\u011Blen\u00ED. Integrovan\u00FD e-learning je tedy vhodn\u00E1 strategie pro uveden\u00ED z\u00E1kladn\u00EDch v\u011Bdeck\u00FDch postup\u016F p\u0159i zpracov\u00E1n\u00ED dat."@cs . . "[3057BC21520A]" . "RIV/00216208:11320/13:10191911" . "Gaining graphical and statistical data processing from remotely controlled experiment"@en . . . "Osvojen\u00ED grafick\u00E9ho a statistick\u00E9ho zpracov\u00E1n\u00ED dat ze vzd\u00E1len\u00FDch re\u00E1ln\u00FDch experiment\u016F" . "D\u016Fle\u017Eitou sou\u010D\u00E1st\u00ED fyzik\u00E1ln\u00EDch experiment\u016F je spr\u00E1vn\u00E9 zpracov\u00E1n\u00ED s vyu\u017Eit\u00EDm statistiky a graf\u016F, a to v\u010Detn\u011B ur\u010Den\u00ED fyzik\u00E1ln\u00EDch konstant \u010Di materi\u00E1lov\u00FDch parametr\u016F z fitu. Nav\u00EDc grafy slou\u017E\u00ED k okam\u017Eit\u00E9mu posouzen\u00ED spolehlivosti a chyb m\u011B\u0159en\u00ED stejn\u011B jako k posouzen\u00ED, zda teorie (model) a experiment\u00E1ln\u00ED data jsou ve vz\u00E1jemn\u00E9m souladu. Graf je z\u00E1kladn\u00ED prost\u0159edek k prezentaci nam\u011B\u0159en\u00FDch hodnot a v\u00FDsledk\u016F. V p\u0159\u00EDsp\u011Bvku p\u0159edstavujeme mo\u017Enosti experimentovat ve vybran\u00FDch t\u00E9matech, kde se pokusy b\u011B\u017En\u00E9 neprov\u00E1d\u00ED (nap\u0159. proto\u017Ee na \u0161kol\u00E1ch chyb\u00ED pom\u016Fcky nebo pokus je p\u0159\u00EDli\u0161 slo\u017Eit\u00FD \u010Di nebezpe\u010Dn\u00FD). V r\u00E1mci strategie v\u00FDuky zvan\u00E9 integrovan\u00FD e-learning p\u0159edpokl\u00E1d\u00E1me, \u017Ee studenti provedou vzd\u00E1len\u00E9 m\u011B\u0159en\u00ED v\u010Detn\u011B c\u00EDlen\u00E9ho z\u00E1znamu a sta\u017Een\u00ED vlastn\u00EDch experiment\u00E1ln\u00EDch dat. D\u016Fraz je v\u0161ak kladen na n\u00E1sledn\u00E9 zpracov\u00E1n\u00ED nam\u011B\u0159en\u00FDch hodnot, nap\u0159. s pou\u017Eit\u00EDm softwaru typu MS Excel. Nap\u0159.: p\u0159i studiu vn\u011Bj\u0161\u00EDho fotoefektu studenti mus\u00ED prolo\u017Eit 5 experiment\u00E1ln\u00EDch bod\u016F p\u0159\u00EDmkou (mimo podprahov\u00E9 frekvence) s c\u00EDlem ov\u011B\u0159it Einsteinovu rovnici pro fotoefekt a vyhodnotit Planckovu konstantu a v\u00FDstupn\u00ED pr\u00E1ci. P\u0159i studiu radioaktivity a z\u00E1kladn\u00EDch zp\u016Fsob\u016F ochrany p\u0159ed ionizuj\u00EDc\u00EDm z\u00E1\u0159en\u00EDm studenti mohou pochopit v\u00FDznam po\u010Dtu opakov\u00E1n\u00ED m\u011B\u0159en\u00ED pro statistick\u00E9 zpracov\u00E1n\u00ED a konvergenci pr\u016Fm\u011Br\u016F k hladk\u00E9 k\u0159ivce, kter\u00E1 m\u016F\u017Ee b\u00FDt porovn\u00E1na s modelovou funkc\u00ED s ohledem na chyby m\u011B\u0159en\u00ED. Hlavn\u00ED v\u00FDhoda vzd\u00E1len\u00FDch experiment\u016F ke studiu radioaktivity je p\u0159\u00EDstup k rozs\u00E1hl\u00E9mu souboru experiment\u00E1ln\u00EDch hodnot, kter\u00E9 byly nam\u011B\u0159eny v nep\u0159etr\u017Eit\u00E9m automatick\u00E9m re\u017Eimu. Speci\u00E1ln\u011B lze vyu\u017E\u00EDt hodnoty p\u0159\u00EDrodn\u00EDho radioaktivn\u00EDho pozad\u00ED k ov\u011B\u0159en\u00ED Poissonova rozd\u011Blen\u00ED. Integrovan\u00FD e-learning je tedy vhodn\u00E1 strategie pro uveden\u00ED z\u00E1kladn\u00EDch v\u011Bdeck\u00FDch postup\u016F p\u0159i zpracov\u00E1n\u00ED dat." . "Pobo\u010Dka JSMF v Nitre, Univerzita Kon\u0161tant\u00EDna Filozofa v Nitre" . "RIV/00216208:11320/13:10191911!RIV14-MSM-11320___" . "1"^^ . . . "Brom, Pavel" . "Osvojen\u00ED grafick\u00E9ho a statistick\u00E9ho zpracov\u00E1n\u00ED dat ze vzd\u00E1len\u00FDch re\u00E1ln\u00FDch experiment\u016F" . "2012-10-17+02:00"^^ .