Let $x\in V_1+V_2$. By definition of $V_1+V_2$, you have $x_1\in V_1$ and $x_2\in V_2$ so that $x = x_1 + x_2$. So...
$x=x_1+x_2=1\cdot x_1+1\cdot x_2\in \operatorname{Span}(V_1\cup V_2)$ since $x_1\in V_1 \subseteq V_1\cup V_2$ and $x_2\in V_2 \subseteq V_1\cup V_2$.
So we have $x\in \operatorname{Span}(V_1\cup V_2)$.
Let $x\in \operatorname{Span}(V_1\cup V_2)$. By definition, there is a finite number (so $1\le i \le n$) of $x_i\in V_1\cup V_2$ and of $\lambda_i\in \mathbb R$ so that $x=\lambda_1\cdot x_1+\dots+\lambda_nx_n$. But each $x_i$ is either in $V_1$ or $V_2$. Let $\alpha_1,\dots,\alpha_p$ be the indices so that $x_{\alpha_i}\in V_1$ and $\beta_1,\dots,\beta_q$ the remaining indices. We have $x=(\lambda_{\alpha_1}\cdot x_{\alpha_1}+\dots+\lambda_{\alpha_p}\cdot x_{\alpha_p})+(\lambda_{\beta_1}\cdot x_{\beta_1}+\dots+\lambda_{\beta_q}\cdot x_{\beta_q})$. And so...
We know that $x_{\beta_i}$ will be in $V_1\cup V_2$ and not in $V_1$ so in $V_2$.
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Since $V_1$ is a subspace and all the $x_{\alpha_i}$s are in $V_1$, $(\lambda_{\alpha_1}\cdot x_{\alpha_1}+\dots+\lambda_{\alpha_p}\cdot x_{\alpha_p})\in V_1$. For the same reasons, $(\lambda_{\beta_1}\cdot x_{\beta_1}+\dots+\lambda_{\beta_q}\cdot x_{\beta_q})\in V_2$.
And so $x\in V_1+V_2$.
the other direction is just the observation that a sum of vectors is a linear combination.
– peter Jan 11 '22 at 19:02