| Judul | Epistemology and Methodology of Research in AI Age / Sulkowski, Lukasz |
| Pengarang | Sulkowski, Lukasz Dacko-Pikiewicz, Zdzislawa Szczepalska-Woszczyna, Katarzyna |
| Penerbitan | London : Routledge, 2026 |
| Deskripsi Fisik | 116 |
| ISBN | 9781003790259 |
| Subjek | EPISTEMOLOGY OF AI RESEARCH METHODOLOGY DATA-DRIVEN RESEARCH |
| Abstrak | Epistemology and Methodology of Research in the AI Age maps how artificial intelligence (AI), digital platforms, and big data reshape the foundations of social science and management research. It connects epistemology and research design to the practical choices researchers now face, from defining questions in data-rich environments to handling algorithmic bias and ethical risk. Written for doctoral students, early-career researchers, and methods instructors, this volume supports dissertation work and methods teaching across sociology, psychology, education, economics, and information science. It also anchors the wider series by setting a shared conceptual and ethical baseline for the volumes that follow. |
| Bentuk Karya | Tidak ada kode yang sesuai |
| Target Pembaca | Tidak ada kode yang sesuai |
| Lokasi Akses Online |
https://www.taylorfrancis.com/books/oa-mono/10.4324/9781003790259/epistemology-methodology-research-ai-age-%C5%82ukasz-su%C5%82kowski-zdzis%C5%82awa-dacko-pikiewicz-katarzyna-szczepa%C5%84ska-woszczyna?context=ubx&refId=785ff3f1-b383-42b4-b2ac-c7d434431518 |
| No Barcode | No. Panggil | Akses | Lokasi | Ketersediaan |
|---|---|---|---|---|
| 160026192 | 001.42 SUl e | Baca Online | Perpustakaan Pusat - Online Resources Ebook |
Tersedia |
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| 001 | INLIS000000000170482 | ||
| 005 | 20260912061135 | ||
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| 100 | 1 | # | $a Sulkowski, Lukasz |
| 245 | 1 | # | $a Epistemology and Methodology of Research in AI Age /$c Sulkowski, Lukasz |
| 260 | # | # | $a London :$b Routledge,$c 2026 |
| 300 | # | # | $a 116 |
| 520 | # | # | $a Epistemology and Methodology of Research in the AI Age maps how artificial intelligence (AI), digital platforms, and big data reshape the foundations of social science and management research. It connects epistemology and research design to the practical choices researchers now face, from defining questions in data-rich environments to handling algorithmic bias and ethical risk. Written for doctoral students, early-career researchers, and methods instructors, this volume supports dissertation work and methods teaching across sociology, psychology, education, economics, and information science. It also anchors the wider series by setting a shared conceptual and ethical baseline for the volumes that follow. |
| 650 | # | # | $a DATA-DRIVEN RESEARCH |
| 650 | # | # | $a EPISTEMOLOGY OF AI |
| 650 | # | # | $a RESEARCH METHODOLOGY |
| 700 | 0 | # | $a Dacko-Pikiewicz, Zdzislawa |
| 700 | 0 | # | $a Szczepalska-Woszczyna, Katarzyna |
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