現代教育学の根本問題[論文]

This paper examines the four most essential theories and concepts as 'hypotheses' to identify the educational reform in the historical development of the modern world. The first 'hypothesis' is Alvin Toffler's "Third Wave" theory (1980). It predicted a fundamental change starting with 'IT revolution.' The second is the "Overproduction crisis" theory, found in Karl Marx’s "Das Kapital". In order to avoid this crisis the global capitalism is obliged to continuously 'invent' tricky policies. As the third hypothesis, the author selected psychiatrist Toshiro Sugiyama’s concept of "Asperger". Sugiyama claims that many of those who play important roles in our society have so-called 'pseudo-Asperger' characteristics. Lastly, the "Reversal denouement kids" coined by Takito Totsuka, a former primary school teacher, was examined. According to Totsuka, some children around the age of 10 show a sudden dramatic development of academic performance. With these four hypotheses in mind, this paper proposes a modern educational reform based on the consciousness of the "plurality of the intellectual developments of the human individuals".1. ｢第3 の波｣仮説(A. トフラー) 2. ｢過剰生産恐慌｣仮説(K. マルクス) 3. ｢アスペルガー｣仮説(杉山登志郎) 4. ｢どんでん返しキッズ｣仮説(戸塚滝登) 5. 今こそ｢人間の知的発達の多様性｣を自覚した教育の創生をtextapplication/pdfdepartmental bulletin pape

決定木を用いた2段階適応型テストの提案

電気通信大学修士2022適応型テストは，受検者の能力値を逐次的に推定し，その能力値に応じて情報量が最大の項目を出題するComputer Based Testingの出題形式である．その利点として，能力値の推定精度を減少させずに出題項目数や受験時間を短縮できる．適応型テストでは，能力推定の漸近分散がフィッシャー情報量の逆数の値に収束することが知られているため，能力推定値に対してフィッシャー情報量が最大の項目を選択する．しかし，テスト開始直後には能力推定値と真の能力値が乖離しているため，最適でない項目が選択される傾向がある．この問題を解決するためにテスト開始直後の能力推定誤差を考慮した項目選択基準が提案されている．しかし，その項目選択基準の多くは，計算に数値積分が必要であるため，極めて計算コストが高く実用化が困難とされている．この問題を解決するために，受検者の全回答パターンに対して決定木を事前に構築し，その決定木を用いて項目を選択する手法が提案されている．しかし，この手法は，出題項目数の増加に伴い，決定木の分枝数が指数的に増加することから，構成可能な決定木の大きさが限定されてしまう問題がある．この問題を解決するために，本論文では，決定木を用いた2段階適応型テストを提案する．本手法は，事前に予測効率の高い項目選択基準を用いて構成可能な最大サイズの決定木を構築する．テスト時は，テスト前半に決定木に基づき項目選択し，受検者の能力値が収束し始めるテスト後半にフィッシャー情報量が最大の項目を選択する．第1段階では，極めて計算コストが高い項目選択基準を用いることによって能力推定誤差の影響を小さくできると期待できる．第2段階では，能力推定値は真の能力値に接近しているため，フィッシャー情報量を用いて項目選択することで高い能力推定精度が期待できる．本論では，シミュレーション実験と実データを用いた実験により決定木を用いた2段階適応型テストの有効性を示す．thesi

Superconductivity of (Pb_0.75W_0.25)Sr_2(RE_0.5Ca_0.5)Cu_2O_z (RE = Nd, Sm, Eu, Gd, Dy, Ho, Er, Tm, Yb, and Y) by Annealing in N_2 Gas

application/pdfJournal of Superconductivity and Novel Magnetism. 2020, 33 (12), P.3667-3672journal articl

Observation of a Resonancelike Structure in the π^+-Ψ' Mass Distribution in Exclusive B → Kπ^+-Ψ' Decays

A distinct peak is observed in the π^±Ψ'invariant mass distribution near 4.43 GeV in B→ Kπ^±Ψ' decays. A fit using a Breit-Wigner resonance shape yields a peak mass and width of M = 4433± 4(stat)± 2(syst) MeV and Γ= 45\begin+18\-13\end(stat)\begin+30\-13\end(syst)MeV.The product branching fraction is determined to be B(B^0→ K^∓Z^±(4430)→ π^±Ψ')= (4.1±1.0(stat)±1.4(syst))×10^{-5}, where Z^±(4430)is used to denote the observed structure. The statistical significance of the observed peak is 6.5σ. These results are obtained from a 605 fb^{-1} data sample that contains 657 ×10^6 B\bar{B} pairs collected near the Υ(4S) resonance with the Belle detector at the KEKB asymmetric energy e^+e^- collider.journal articl

Search for CP Violation in the Decay B0→D*±D∓

journal articl

Reconstruction of triplet trees.

(A) A triplet tree with the indicated depths (X = number of cell divisions) between the root and the leaves and between the root and the branch. (B) Reconstruction accuracy as a function of the number of STR loci and the depth of the leaves (number of cell divisions from the root). Results are shown for STR mutation rate of 10−4 mutations per locus per cell division. The graph shows that fewer mutations are needed when there are more cell divisions. The results are averaged over 1000 repeated stochastic simulations. (C) Same as (B) but using parameters that represent future enhancements (see Methods).</p

Experiment requirements for identifying that two cell groups have different depth on the cell lineage tree.

<p><b>(A)</b> Cells from two cell groups are sampled from the cell lineage tree. The depth (number of cell divisions since the root) of cells of group A is X and the depth of cells of group B is X+Y. <b>(B)</b> The heatmap colors represent the statistical power, i.e., the probability of detecting a depth difference between cells from A and cells from B when such difference does exists, as a function of the number of cells (x-axis) and number of loci (left y-axis) analyzed. The probability of falsely identifying depth difference when it does not exist (type I error) is 5% (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004983#sec007" target="_blank">Methods</a>). White line marks the area of power = 95%. Black line indicates the overall analysis cost as shown in the right y-axis–both lines have the same x-axis and every point in the black line represents the cost that corresponds to the combination of the number of loci and number of cells as represented by the white line. In this case, for X = 40 and Y = 10, a minimum cost is obtained using about 65K loci and 90 cells. The same power can be obtained using about 35K loci and 200 cells but the cost increases by about 50%. Results are averaged over 1000 stochastic simulations using STR mutation rate of 10⁻⁴. <b>(C)</b> Cost optimization for the number of loci and number of cell samples needed for statistical power of 95%, for various values of X and Y. Numbers in parenthesis indicate the number of cell samples and number of required loci respectively. <b>(D)</b> Same as (B) but using parameters that represent future enhancements affecting both the quantity and the quality of the signal (see <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004983#sec007" target="_blank">Methods</a>). <b>(E)</b> Same as (C) but using parameters that represent future enhancements.</p