Remote Laboratory, Based on Raspberry Pi, to Facilitate Scientific Experimentation for Secondary School Students

The pandemic caused by COVID 19 forced education systems to offer their services remotely due to social distancing policies. This article discusses research results on the development of remote laboratory architectures to deliver scientific experimentation in the area of physics for secondary school students using desktop computers or mobile devices.The design of the remote laboratory is based on the Raspberry Pi device, using various sensors and a graphical interface through which access and communication is given.The purpose of the development of this remote laboratory is to provide teachers and students of secondary education access to the development of remote activities for scientific experimentation in physics courses, using low-cost devices and free software.

Co-Designing Urban Carbon Sink Parks: Case Carbon Lane in Helsinki

In order to achieve the goals of carbon (C) neutrality within next 20 year, municipalities worldwide need to increasingly apply negative emission technologies. We focus on the main principles of urban demonstration areas using biochars for C sequestration and explore the lessons learned from a co-creation process of one such park, Hyväntoivonpuisto in Helsinki, Finland. Demonstration sites of urban C sinks in public parks must be safe, visible and scientifically sound for reliable and cost-effective verification of carbon sequestration. We find that different interests can be arbitrated and that synergy that emerges from co-creation of urban C sink parks between stakeholders (scientists, city officials, companies, and citizens) can result in demo areas with maximized potential for impact, dissemination and consideration of principles of scientific experimentation.

Empiricism Must, but Cannot, Presuppose Real Causation

In this article, I put forward a basic philosophical claim: empirical scientific knowledge, that is, knowledge generated in experimental and observational practices, presupposes real causation. My discussion exploits two core notions from the philosophical analysis of scientific experimentation and observation: the aim of realizing object-apparatus correlations and the required control of the relevant interactions between environment and experimental or observational system. The conclusion is that, without the notion of real causation, acquiring epistemically sound empirical knowledge is impossible. Several empiricist objections to this conclusion are discussed and refuted. As a consequence, empiricism faces an unsolvable dilemma: either it cannot account for empirical knowledge or it should accept the existence of unobservable but real causal interactions.

Introduction

The work begins with a look at the tabletop experiment Richard Feynman performed before a presidential commission investigating the space shuttle Challenger disaster. The case introduces the work’s leading questions—what do good experiments accomplish? What is the relation between experiments and experience, or between experience and knowledge? A distinction between two versions of empiricism plays a thematic role in the work. One version is “problematic,” another “theorematic,” using terms from Euclid for a difference in what these empiricisms expect from experience. For theorematic empiricism experience is ultimate evidence, its value probative (proof, demonstration, verification). Problematic empiricism eschews the idea of ultimate evidence, and from experience expects superior performance and a successful solution to a problem of knowledge. It is this problematic empiricism that is associated with scientific experimentation (the argument of Part I), as well as with the so-called radical empiricists (the argument of Part II).

Context-SE: Conceptual Framework to Analyse Context and Provenance in Scientific Experiments

Managing contextual and provenance information plays a key role in the scientific domain. Activities which are carried out in this domain are often collaborative and distributed. Thus, aiming to examine and audit results already obtained, researchers need to be aware of the actions taken by other members of the group. Contextual and provenance information are essential to enhance the reproducibility and reuse of experiment. The goal of this work is to present a conceptual framework that provides guidelines capable of supporting the modeling of provenance and context in a software ecosystem platform to support scientific experimentation. Preliminary results are also presented when the proposed solution is used to design software ecosystem platform components.