As I indicated in another thread the basis of elementary tensors $e^j \otimes e_i$ of $V^{\ast} \otimes V$ can be identified with the basis of elementary matrices $E_{ij}$ of $\text{Hom}(V,V)$.
Note that this identification uses a basis choice for $V$, but it is possible to do this in a completely basis-free manner.
One thing to remember is that linear functionals (at least for finite-dimensional vector spaces) are pretty much just "glorified inner products". That is, every element $f \in V^{\ast}$ can be thought of as the function:
$\langle u,\_\rangle$ for some vector $u$.
For example, we have $e^j = \langle e_j,\_ \rangle$ for the standard basis for $V$.
***Note*** Vector spaces, of course, do not always come equipped with a "natural" inner product. However, any non-degenerate bilinear form $B$ can be used to induce an isomorphism (only in the finite-dimensional case, n.b.) between $V$ and $V^{\ast}$, and the "go-to" non-degenerate bilinear form in an inner product space is, of course, the inner product (BUT...in complex vector spaces, it is often more convenient to use a sesquilinear form, due to the peculiarities of the complex conjugate).
In particular, it is natural to identify the 1-form (dual basis element) $e^j$ with the $j$-th projection function.
*******
Computing the values of these mappings is often tedious. $\alpha(e^i \otimes e_j) (v)$ basically takes the $i$-th coordinate of $v$ (in the given "$e$" basis) and sticks it in the $j$-th slot, with every other coordinate 0. To extend this to the entire tensor $t$ we extend by (multi-, in this case, bi-) linearity.
So if:
$t = (e^1 + e^2) \otimes (e_3 + e_4) = e^1 \otimes e_3 + e^1 \otimes e_4 + e^2 \otimes e_3 + e^2 \otimes e_4$
Then:
$\alpha(t)(v) = 2e_3 + 2e_4 + 3e_3 + 3e_4 = 5e_3 + 5e_4$
or, perhaps more understandably, relative to our given basis $S$ of $V$:
$[T]_S([v]_S) = [T]_S(2,3,2,3)^T = (0,0,5,5)^T$
(if I have done my arithmetic correctly), that is relative to the given basis, our linear mapping $T$ has the matrix:
$\begin{bmatrix}0&0&0&0\\0&0&0&0\\1&1&0&0\\1&1&0&0 \end{bmatrix}$